"Through our partnership with Intel, we have helped clients improve their total cost of ownership and performance by leveraging best in class hardware and software. Intel’s seamless product integration has allowed our customers to provide the highest quality end user experiences. Intel’s developer documentation makes it simple to share software, such as the Intel® AI Analytics Toolkit (powered by oneAPI), cnvrg.io*, SigOpt*, and many more, with our massive data science community. Intel incorporates ease of use in their product lineup. With oneAPI, engineers can train, score, and deploy models in a production environment with improved accuracy and performance. This consistent and rewarding experience across the product suite makes Intel a competitive choice for AI workloads."
"With the help of Intel, we were able to train, optimize, and deploy a machine learning model in less time and at a lower operational cost than available alternatives, enabling us to get to market fast with a powerful solutions that's optimized for Intel® architecture."
"Through a strong and close partnership with Intel, we have helped our customers accelerate their online service greatly with Intel technology. By leveraging and integrating the key features of Intel® Neural Compressor and Intel® Extension for Transformers* into Alibaba Cloud* PAI-Blade, we offer extremely high performance and reduce the total cost of ownership (TCO). These tools provide a high-performance solution for model optimization and optimized-aware inference, which help PAI-Blade extremely easy to adopt optimization like int8 for better performance without accuracy loss. We believe our ongoing collaboration with Intel will bring more benefits to AI workloads and services."
"E-HPC provides individual users, education and research institutions, and public institutions with a fast, elastic, and secure cloud compute platform. With the Intel® oneAPI toolkit, E-HPC can help customers build a high-performance, profiling computing platform on Intel® Xeon® Scalable processors."
"[The] Intel® AI Analytics Toolkit was extremely easy to use. With just a few hours of mostly configuration work, we were able to use [it] to significantly improve the performance of our machine learning code. This allowed us to analyze larger datasets on the same size compute resources and significantly reduce the carbon footprint of our model training. It was so easy to use, secure, flexible and scalable that you don't have any reason to not try it today."
— Arijit Sengupta, founder and chief executive officer (CEO)
"oneAPI is an exciting initiative, and our Singapore AI engineering team is already using Intel oneAPI Beta tools for our 100 Experiments (100E) and AI Apprenticeship programs. We’re looking to the future where Intel® oneAPI tools will allow us to focus on building cutting-edge AI solutions and products for our industry partners with consistent interfaces and tooling."
— Laurence Liew, director, AI Industry Innovation & Makerspace, AI Singapore Engineering Team
"Allegro is a proud participant in Intel's oneAPI Beta program. We are pleased to collaborate with Intel to drive acceleration of computer vision and perception for edge devices, IoT and other use cases, and to support [Data Parallel C++] DPC++ with heterogeneous hardware environments in real-life deployments."
— Nir Bar-Lev, chief executive officer (CEO) and cofounder, Allegro
"By integrating Intel® oneAPI Data Analytics Library (oneDAL) and Intel® AI Analytics Toolkit tools into Allegro Trains, Allegro AI offers better performance and optimized use of cloud instances."
"We are excited to partner with Intel to bring oneAPI to our user community. oneAPI's open, standards-based, unified programming model accelerates the development of high-performance data science, ML, and AI tools that target a broad range of CPUs, GPUs, FPGAs, and other accelerators. Our ongoing partnership with Intel—providing prebuilt binary packages—simplifies access to oneAPI-based applications, both for developers of such tools and the practitioners using them."
— Cheng Lee, principal software engineer, Anaconda*
Using the Intel® Integrated Performance Primitives (Intel® IPP) ACF Performance Results are now providing 127x faster training performance and 66% reduction in overall cost of running the training algorithm in cloud environment and with Intel® oneAPI Data Analytics Library (oneDAL) XGBoost was able to achieve 4x faster inferencing time.
"Intel oneAPI has enabled us to deliver outstanding performance and value to customers of our engineering simulation software. To reach the next level of performance, we are delighted to see this partnership continue to grow."
To build a high-performance media pipeline on Intel® Data Center GPU Flex Series GPU, we use Intel® DPC++ Compatibility Tool to migrate multiple kernels from CUDA* to C++ with SYCL*, and created a new single, portable code that support multiple platforms. The migrated code efficiently runs on Intel Data Center GPU Flex Series and achieves competitive performance with lower power compared with current GPU solution.
"We're seeing encouraging early application performance results on our development systems using Intel® Max Series product family GPU accelerators—applications built with Intel® oneAPI compilers and libraries. For leadership-class computational science, we value the benefits of code portability from multivendor, multiarchitecture programming standards such as SYCL* and Python* AI frameworks such as PyTorch* accelerated by Intel libraries. We look forward to the first exascale scientific discoveries from these technologies on the Aurora system next year."
— Dr. Timothy Williams, deputy director, Argonne Computational Science Division
"The future of advanced computing requires heterogeneous hardware to maximize the computing power needed for exascale-class workloads. The oneAPI industry initiative Intel is spearheading will ensure that programming across diverse compute architectures is greatly simplified."
— Rick Stevens, associate laboratory director, Computing, Environment, and Life Sciences, Argonne National Laboratory and professor of computer science, University of Chicago
"Pursuing scientific discoveries on the very fastest architectures should not be limited by closed, proprietary software programming models. Having a common open standard is the most efficient path to enabling performance portability across DoE’s next-generation supercomputers. We want to make our capabilities accessible to all researchers—using DPC++ supporting SYCL* does that."
— Kevin Harms, team lead for I/O Libraries & Benchmarks, Argonne Leadership Computing Facility (ALCF)
“CRK-HACC is an N-body cosmological simulation code actively under development. To prepare for Aurora, the Intel® DPC++ Compatibility Tool allowed us to quickly migrate over 20 kernels to SYCL. Since the current version of the code migration tool does not support migration to functors, we wrote a simple Clang tool to refactor the resulting SYCL source code to meet our needs. With the open source SYCLomatic project, we plan to integrate our previous work for a more robust solution and contribute to making functors part of the available migration options."
— Steve (Esteban) Rangel, Hardware/Hybrid Accelerated Cosmology Code (HACC), Cosmological Physics & Advanced Computing, Argonne National Laboratory
"Analytics Zoo and the Intel® AI Analytics Toolkit with the Intel® oneAPI Data Analytics Library (oneDAL) helped reduce end-to-end data processing time and improved our prediction model’s accuracy significantly for AsiaInfo 5G network intelligence including customer satisfaction analysis, power saving for 5G base station and user location analysis."
— Duozhi Zhu, general manager of 5G Network product R&D department, AsiaInfo Technologies Limited
"Our successful collaboration with Intel centered around the optimization of state-of-the-art computer vision models for our UI automation tool, in particular the analysis of user interfaces. Together, we focused on performance optimizations of our pipeline powered by oneAPI with OpenVINO™ on Intel® CPUs, achieving considerable speedups in inference times. This secures fast executions of automations, and thus leads to significant time savings for our customers. We are thankful for the fruitful cooperation!"
— Jonas Menesklou, chief executive officer (CEO) at askui
"We decided to collaborate on the integration of Intel® Open Image Denoise. We had strong demand to integrate Intel Open Image Denoise from some of our customers who are praising its speed and quality. Arnold already ships with two denoisers, which we thought it would give our users an interesting additional choice, Intel Open Image Denoise being deep learning accelerated and running on CPU. In Arnold 6 we had recently introduced a new post processing framework called images. We used it for 2D post effects such as glow or color correction and it’s the perfect place to integrate Intel Open Image Denoise. The implementation was very easy and we were very happy with the results. The quality and speed of Intel Open Image Denoise really helps with interior scenes. Because we can denoise so quickly, it can also be used in IPR [interactive photorealistic rendering]… In conclusion, I’d like to thank Intel for these amazing contributions to Arnold. We are really excited about the ongoing collaborations with the Arnold team at Autodesk."
— Frederic Servant, senior software development manager
"PaddlePaddle* is the first AI deep learning framework in China to integrate with the traditional molecular dynamics’ software LAMMPS and AI-based potential function software DeePMD kit. Based on Intel® Xeon® [processors] and oneAPI technology with Intel® oneAPI Math Kernel Library (oneMKL) and Intel® oneAPI Deep Neural Network Library (oneDNN), the breakthrough progress in the whole process from training to inference has been realized, and the performance has reached the same level of a fellow deep learning framework, enabling the design and development with AI applied to materials science."
"Ben-Gurion University is pleased to take part in Intel’s oneAPI Beta. We believe a unified and open programming model is imperative for helping us more efficiently build advanced software solutions on diverse architectures in our AI research. This enables students, developers and researchers to learn how to build advanced software and scale it to a variety of data center-size accelerators for tackling tough problems in AI, analytics, physics, computational chemistry and many other fields."
— Professor Lior Rokach, Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev
"Using Intel technology, we’re now able to render more than 10 billion images in 16 weeks…by working with Intel on the oneAPI Rendering Toolkit, we’ve been able develop proof of concepts on cost-efficient methods for creation rendered images and user experiences for the future."
"Intel's oneAPI toolkit has demonstrated powerful performance and good compatibility in GeoEast software applications, and has provided us with important help in the further exploration of heterogeneous computing."
"We have been using Intel® Parallel Studio XE for years. It is exciting to see that Intel is building a comprehensive and powerful ecosystem with Intel® oneAPI Base Toolkit and Intel® oneAPI HPC Toolkit, and we are going to migrate our whole development environment to oneAPI. It unifies the programming language on different platforms and will definitely simplify the development progress and downgrade the developing difficulty."
"The Intel® oneAPI Data Analytics Library (oneDAL) is central to our machine learning platform that is used for supervised object labelling in biological image analysis. After switching to oneDAL SVM, we found it to give superior speed on a low-end CPU compared to ThunderSVM on an NVIDIA* GeForce GTX 1080. Another key to our work with oneDAL is the sheer number of different ML, processing, and modeling methods in one library. oneDAL essentially has all the batteries integrated, while offering good to great performance in everything we have tried so far.”
— Mario Emmenlauer, founder and CEO, BioDataAnalysis GmbH
"Some application codes which have historically been implemented on CPUs or GPUs actually run more efficiently on FPGAs. Until now, porting these applications to FPGAs has been a significant investment requiring expert hardware programmers. oneAPI is a welcome, bold initiative that introduces a unified software programming model capable of supporting Intel® Stratix® 10 and Intel® Agilex™ FPGA accelerators. Fundamentally, oneAPI opens up the compelling benefits of FPGAs to customers who are software-oriented."
— Craig Petrie, vice president of marketing, BittWare – a Molex company
"With a smooth learning curve from C++, minor code divergence, and a common codebase, the leading-edge Intel® oneAPI technology reduces the barriers of programming on different architectures. This allows maximum flexibility to harness all the computational capacity of HPC clusters."
— Khaled Elamrawi, president, Brightskies Inc.
"With strong commitment and continuous support from Intel, Brightskies was able to fully utilize the Intel® oneAPI capabilities. In addition, the expected future enhancements promise a significant leap in the performance of seismic imaging and velocity model building techniques."
"Caliper has harnessed the power of the 13th generation Intel® Core™ i9 processors and Intel® VTune™ Profiler to develop the most powerful and versatile transportation planning and simulation software. With our TransCAD* and TransModeler* products, we have achieved market-leading computational performance on Intel processors exploiting multithreading and distributed processing buttressed using the Intel VTune Profiler tool to optimize the performance of our software. The ability to simulate traffic at orders of magnitude faster than real time offers enormous potential for reducing congestion in the world’s cities, and the creation of citywide digital twins for transportation paves the way for successful intelligent transportation systems and effective deployments of connected and automated vehicles."
— Howard Slavin, PhD, president, Caliper Corporation
"We are honored to be among the vanguard of institutions chosen to be an Intel oneAPI Center of Excellence, ensuring we build on our long-standing collaboration on in situ visualisation and code modernisation as we prepare to study the universe at exascale. We’re committed to flexible platform-independent programming paradigms so that we can do more with fewer people, focusing on trying out new ideas and new algorithms for our cosmology workflows. The oneAPI development tools offer us a fast pathway on to the widest range of HPC architectures, especially the latest GPU accelerators, so we can respond to the flood of new cosmological data sooner."
"The University of Cambridge Research Computing Service supports world-leading research in science, technology, and medicine where we see the need for large-scale data-driven discovery platforms with converged capability for simulation, data analytics, and AI. If these computation discovery platforms are to advance in step with the ambitions of the science projects that drive them, we will need ever more energy-efficient systems that rely increasingly on heterogeneous compute elements to help solve the world’s biggest scientific challenges. The promise of oneAPI to deliver a single programming environment across multiple compute architectures is a vital tool to unlock the promise of heterogeneous computing. Here science communities can leverage investments in code development across multihardware platforms helping advance performance gains from different hardware targets and also making future hardware targets more accessible."
— Paul Calleja, director of Research Computing Service, Cambridge University
"As a long-standing partner of Intel, Canonical is excited by oneAPI’s vision of a cross-industry, open, standards-based unified programming model. Modern enterprise and cloud data centers increasingly incorporate domain-specific accelerators, and oneAPI is the logical next step that enables ecosystem adoption of cross-architecture programming. Developers can leverage oneAPI’s cross-architecture interface to optimize application performance across the spectrum of supported accelerators, while the libraries for AI, ML, analytics, and high-performance computing will help reduce time to market for enterprises."
— Dean Henricksmeyer, VP Cloud Products Engineering, Canonical
"Intel’s oneAPI initiative addresses the ever-present challenge of porting code to new hardware targets for the developer community. Long-term, the initiative will help meet the demands of converged computing and unify the development experience for heterogeneous architectures while promoting code reuse. This will speed adoption of new architectures and accelerate the convergence of [high-performance computing] HPC and AI. With [the Centre for Development of Advanced Computing] C-DAC at the forefront of addressing India’s HPC and AI technology and application demands, we welcome this approach and look forward to applying it in our organization."
— Dr. Hemant Darbari, director general, C-DAC
"We are happy to take our partnership with Intel yet another step forward. With heterogeneous computing becoming order of the day, oneAPI will ease the efforts related to targeting the same algorithm for a variety of architectures based on CPUs and accelerators based on GPUs and FPGA. We would be leveraging on our connect with users of NSM facilities and through NSM Nodal centers, to equip them with knowledge of oneAPI and its usage, so that they are able to get optimum performance from the platform they are using."
"C-DAC developed our seismic acoustic modeling application for 2D heterogeneous mediums using finite-difference time-domain modeling, which plays an important role in the exploration of natural energy resources such as oil, gas, and minerals. At C-DAC we develop our open source seismic modeling application (SeisAcoMod2D) was written in CUDA*, limiting our alternatives. To open up vendor and architectural alternatives, we chose to migrate to SYCL* using the SYCLomatic migration tool. Our code now also runs on the Intel® Data Center GPU Flex Series. As we look forward, using Intel® Xeon® Max Series and the Intel® Data Center GPU Max Series presents us with new upgrade paths without the need for code changes."
"For our HPC chemical simulation program EMPIRE, we successfully moved our Fortran code, which was designed explicitly for fast parallel CPU-performance, from the Intel® Fortran Compiler Classic to the modern Intel LLVM* based Intel Fortran Compiler without any modifications of the source code. The transition to Intel Fortran Compiler allowed us to efficiently extend our code to leverage GPUs using OpenMP* offloading. We were delighted to see that oneAPI easily allowed both the implementation and performance optimization on the Intel® Data Center GPU without major code changes or GPU-specific proprietary solutions. The performance for the self-consistent-field calculations that form the core of semiempirical molecular-orbital calculations gives both impressive speedup and scaling on the Intel Data Center server GPUs and achieves competitive performance compared to currently available GPU solutions."
— Timothy Clark, chief executive officer (CEO) at Cepos InSilico GmbH; professor
"Scientists at the CERN Large Hadron Collider (LHC) project are working towards new scientific discoveries that will require them to analyze unprecedented data volumes on the most powerful HPC systems worldwide. The oneAPI concept of a unified programming model, built on open industry standard specifications, will allow for a seamless software development process for utilising heterogeneous processing hardware infrastructures. As an early participant in Intel’s Beta programme, we are very interested in the prospects oneAPI is offering for the future of software development in our field."
— Dr. Markus Elsing, group leader, CERN ATLAS Data Processing Group
"One of the major problems facing developers today is disparate programming environments and little code re-use opportunities across different types of hardware. A single programming environment that could render code without sacrificing performance across multiple hardware types is a difficult, yet important challenge. Intel oneAPI appears to be a significant step in the right direction, promising code portability without compromising the ability to tune performance for CPUs and accelerators, and making hardware transitions considerably less risky and error prone. We are therefore considering oneAPI for high energy physics (HEP) workloads."
"We are actively working on oneAPI as the unification of offload programming models, such as the Data Parallel C++ (DPC++) and OpenMP*, will increase our productivity. It will reduce our production and maintenance costs, while maintaining a very good level of production performance."
— Jean-Yves Blanc, IT chief architect, Subsurface Imaging IT Strategy, CGG
"We do everything we can to maximize performance from every core in our processor system…The Intel® Embree team [is] great to work with… as they really try to put in things that make our lives easier as developers, as well as our customers. When they heard of memory requirement needs being high on displacement, they produced a new displaced quad primitive that we put into Corona. The result: we got up to a 90% reduction in memory††, which meant that the Corona users could now use displacement almost for free, really enrich their scenes without increasing their RAM."†
— Phil Miller, vice president of product management, Chaos Group
"The Faculty of Mathematics of Charles University is thrilled that such a cooperation has been set up [becoming an Intel oneAPI Center of Excellence], which is a significant asset for the computer science landscape in the Czech Republic. We are looking forward to seeing the results from this effort, which will combine novel technologies from several directions into something that significantly moves the state of the art forward in image synthesis."
— Alexander Wilkie, head of the computer graphics branch of the Computer Graphics Group, Charles University
"Cineca* is enthusiastic about the work Intel is undertaking with the oneAPI software stack, which supports open specifications for a single cross-architecture development model. Building on that work, Cineca is investing in community codes like Quantum Espresso to enable it for future exascale solutions on multiple types of architectures."
— Carlo Cavazzoni, head of HPC solutions and architectures, Cineca
"When we set out to make The Addams Family2*, we wanted it to be bigger, better, and more fun than the first movie. To achieve that, we needed advanced tools and technology for our artists to create the ground-breaking, beautiful visuals to accompany our story. We were so fortunate to partner with Intel on this, and get our artists everything they needed to achieve the work we wanted for the movie."
— Laura Brousseau, codirector of The Addams Family 2*, Cinesite
"We used Intel® Open Image Denoise on every shot of The Addams Family 2 and were able to gain a 10% to 20%—and sometimes 25%—efficiency in rendering, saving thousands of hours in rendering production time.‡‡‡ That allowed artists to focus more on the creative aspect of movie making, which meant they were able to spend their time lighting shots and making the visuals more intricate and complex, rather than spending time troubleshooting sample noise."
— Kenny Chang, head of Lighting at Cinesite
Cinesite Brings Creepy & Kooky Storytelling to Life Using Intel® Open Image Denoise: Case Study | Video
"Codeplay* Software is a world pioneer in enabling acceleration technologies used in AI, HPC, and automotive. Codeplay has been heavily involved in the definition of SYCL* and helped to grow the ecosystem, providing evaluation platforms, resources, and workshops. With oneAPI building on SYCL, Intel gains all the benefits of an open-standards-based ecosystem, while enhancing with extensions to embrace features and performance available to modern C++ developers."
— Andrew Richards, founder and chief executive officer (CEO), Codeplay Software
"Codee* is a world-first solution providing a systematic, predictable approach to enforce C, C++, Fortran performance optimization best practices for CPUs and GPUs. Notably, it is the perfect complement to the best-in-class Intel® oneAPI DPC++/C++ Compilers and runtimes."
— Manuel Arenaz, founder, chief executive officer (CEO), and chief technology officer (CTO), Codee
“Finding a productive way to run the Rodinia Benchmark across different architectures–CPUs, GPUs, and migrating to new architectures–is extremely important. oneAPI clearly became our best solution for heterogenous hardware. We ported the Rodinia Benchmark from CUDA* to SYCL* using the Intel® DPC++ Compatibility Tool, and 20 of 23 benchmarks migrated easily without much programming effort and achieving nearly the same performance. SYCL provides ease in portability and significant time savings allowing us to perform the parallel application on several CPU- and GPU-based devices without vendor restriction. We are currently evaluating Intel’s upcoming Xe GPUs and so far are experiencing positive results.”
— Carlos Garcia Sanchez, assistant professor, University Complutense Madrid
"The Intel® oneAPI Base & AI Analytics toolkits improved our 3D model reconstruction's performance by up to 9x on an Intel® Xeon® platform compared to our existing GPU solution."
—Mr. Gao, R & D general manager, Daspatial†
"Intel provides the backbone for optimized AI workloads through tools and framework optimizations that are powered by oneAPI. Running DataRobot* on Intel makes it possible for our common customers to not just talk about AI but to embrace it as a core part of their enterprise’s business and culture."
"oneAPI includes all the tools that data scientists and developers are already using and familiar with around AI, so they can unlock these new capabilities in their silicon…oneAPI is ushering in a new era of competitiveness, which is good for the industry. My customers will have the ability to develop their applications across CPUs and new upcoming discrete GPUs."
— Michael Boros, senior strategist, Cloud Solutions Group/AI, Dell
"Digital Cortex* and Intel are making XPUs as easy as CPUs so you can use the right device for each workload. No one device is the best for every job, so we include all of them and, with the power of oneAPI, use each for when it's best. Digital Cortex's function as a service gives you an API to awesome, Intel-powered, performance."
— Chris Esworthy, chief operating officer (COO), Digital Cortex
“We have been working with Intel® VTune™ Profiler for many years. No other performance profiler provides this level of detail, convenience, and stability. It has helped us in many situations immediately and accelerates performance analyses. significantly. Dive achieved 1.5x speedup in vectorization using Intel® CPU and Intel® oneAPI toolkits."
"Current HPC codes often run efficiently either on multicore nodes or accelerators, but typically struggle to balance between the two paradigms and to get the best performance out of both architectures working together. The added value and big promise behind oneAPI is that we get one programming model for all parts of the machine and then can let algorithms decide dynamically which steps of the code to run where."
—Tobias Weinzierl, principal investigator, Durham University
"On the recently released Modo 14.1, our customers are reporting amazing rendering performance with Intel® Embree ray tracing library and Intel® Open Image Denoise that previously would have only been available through high-end GPUs. This really packs a one-two punch to those costly render times…that all our users can appreciate."
— Shane Griffith, director of product digital design, Foundry
"With oneAPI, you can now develop these solutions once but then actually deploy them with very minimal rework on this very heterogeneous compute fabric with many different computer architectures. That's really powerful and that can really be a game changer for us."
— Roshni Bhagalia, vice president, Product Management for the Edison Platform
"We see oneAPI as potentially becoming a de facto industry standard to program heterogeneous compute systems and we believe that using oneAPI actually provides us with ability to port our code across multiple architectures and even multiple vendors, saving potentially millions of dollars in configuration cost as well as many, many years of engineering effort that we would have to invest if we'll have to completely rewrite this code from one programming model to another."
— Evgeny Drapkin, chief engineer of Compute
"A unified programming model like Intel’s oneAPI can go a long way in accelerating the hardware and software ecosystems. We especially welcome how Intel is driving this as an open initiative and look forward to working closely with them to increase adoption in a collaborative manner."
— Dani Pinkovich, algorithm group manager, GE Healthcare
"We're excited to collaborate with Intel on oneAPI, which delivers a single programming model that can address our customers’ production needs across compute and memory intensive workloads, at speed and scale across various types of architecture and accelerators. oneAPI will enable GigaSpaces'* customers to deploy end-to-end machine learning and deep learning pipelines from training and validation to the inference and adaptive learning stages."
— Yoav Einav, vice president of product, GigaSpaces
"Collaborating with Intel and using the Intel® oneAPI HPC Toolkit has been instrumental in helping our customer engineers understand in depth our customers' HPC workloads and performance on GCP instances. We recommend using Intel® MPI for best performance, and tools such as Intel® VTune™ Profiler and Intel® Advisor to help better understand performance optimizations and how to best migrate your workloads to the cloud."
"Hasty* and Intel are working together on computationally heavy vision AI tasks like small object detection and massive image analysis or a combination of these two challenges. Unlocking this capability will be a step-wise shift in the barrier of vision AI for critical industries such as agriculture, disaster recovery, logistics, and medical, to name a few. Our work has focused on the benefits of using CPUs and Intel® AI Analytics Toolkit for critical machine learning tasks like inference and data mining."
"Having an open, unified programming model for cross-architectural software development will be highly beneficial for future research and for developing cutting-edge scientific applications, especially in areas such as high performance computing, data analytics, and AI and machine learning, among others. As a university computing centre that values open standards, open exchange, and cooperation, we are happy to support to this effort."
— Prof. Dr. Vincent Heuveline, CIO of Heidelberg University and managing director of the Heidelberg University Computing Centre (URZ)
"The cooperation with Intel has empowered HelpMeSee* to achieve a much higher level of performance for the HelpMeSee Eye Surgery Simulator and simulation-based training program. By leveraging the Intel® Extreme Tuning Utility (Intel® XTU) and the Intel® VTune™ Profiler, which is used as part of Intel® oneAPI Base Toolkit (Base Kit), we've been able to gain deeper understanding and fine-grained control over many CPU parameters resulting in significant improvements on various aspects of our simulation software stack. Through our collaborative work with Intel, HelpMeSee’s Global Innovation and Technology team has gained greater focus on performance optimization. This commitment will be key in helping us provide the finest quality virtual reality training for medical professionals around the world. Going forward, we are trying to explore other components of the Base Kit, which can help us to further optimize and improve the performance of our simulator software."
"We are approaching the exascale era, which is defined by data growth and converged HPC, AI, and analytics workloads to unlock greater value, discovery, and accelerate innovation. Customers are requiring development tools to address varying and data-intensive workloads running on complex, diverse architectures. By continuing our long-standing partnership with Intel and supporting oneAPI, our customers are gaining tools to optimize applications and speed market delivery through unified programming and simplified software development across a range of HPE technologies, including compute solutions such as CPUs, GPUs, FPGAs, and AI accelerators."
— Peter Ungaro, senior vice president and general manager, HPC and AI, HPE
"We at HippoScreen* have been able to take advantage of the software optimizations in Intel® Extension for Scikit-learn* and Intel® Optimization for PyTorch* to accelerate the build times for the AI models in our customized EEG Brain Waves analysis system by 2.4x. The Intel® VTune™ Profiler allowed us to quickly identify and rework threading oversubscription issues that were holding back our algorithms. The tools and framework optimizations in the Intel® oneAPI Base & AI Analytics Toolkits provide a performant and productive way for us to build AI pipelines while also being efficient and adaptable to workflow changes."
Hisense Adopts Intel® oneAPI Base Toolkit (Base Kit) to Develop Its New Ultrasound Imaging Application
Hisense’s new ultrasound imaging platform consists of GPUs and CPUs in its computing architecture for ultrasound desktop and portable devices. We not only migrated key CUDA* kernel functions to SYCL* to run on current and future generations of Intel® CPUs using the Intel® DPC++ Compatibility Tool, but also simplified programming for our cross-architecture systems. Using Intel® oneAPI toolkit components including the Intel® oneAPI DPC++/C++ Compiler, Intel® Integrated Performance Primitives (Intel® IPP), Intel® oneAPI Math Kernel Library (oneMKL), and Intel® oneAPI Threading Building Blocks (oneTBB) has helped in reducing the total post-processing time in the ultrasonic system for signals and images. Intel oneAPI toolkits help us simplify our development efforts and deliver better products to our end users.
"At Hugging Face*, we are focused on making the latest advancements in AI more accessible to everyone by making state-of-the-art machine learning models more efficient and cheaper to use. We're proud to partner with Intel to make it easy for the community to get peak performance, faster model training, and advanced AI deployments on powerful Intel® hardware devices through close integration of the free open source Optimum library with components in Intel’s oneAPI-powered AI software portfolio including OpenVINO™ and Intel® Neural Compressor."
"Integrating TensorFlow* optimizations powered by Intel® oneAPI Deep Neural Network Library into the IBM Watson* NLP Library for Embed led to an upwards of 165% improvement in function throughput on text and sentiment classification tasks on 4th gen Intel® Xeon® Scalable processors. This improvement in function throughput results in a shorter duration of inference from the model, leading to quicker response time when embedding Watson NLP Library in our clients' offerings."
— Bill Higgins, director of development for Watson AI in IBM Research
"We are working on developing scalable algorithms for diverse parallel computing architectures. The standards-based open oneAPI specification will simplify development complexity by enabling one software abstraction across heterogeneous architectures, while allowing hardware-specific tuning for optimal performance. We have started exploring the Intel® oneAPI toolkit Beta, and are confident that the oneAPI programming model will mature and become a standard."
— Professor Sashikumaar Ganesan, associate professor and chair, Department of Computational and Data Sciences, Indian Institute of Science
"The oneAPI initiative to unify the developer experience across diverse architectures will address the need of the hour for AI, especially in the scientific community where new applications are being developed using the best-suited heterogeneous hardware choices. As an institution focused on scientific research, we look forward to engaging with Intel on oneAPI to evaluate how it can help our AI and [high-performance computing] HPC researchers drive faster innovation by harnessing the capabilities of a range of modern hardware architectures today and in the future through simplified programming interfaces."
— Goldi Misra, chief technology officer, IISER Pune, India
"We eagerly look forward to the oneAPI initiative, and the effort to build a platform-inclusive programming approach that will help domain experts improve utilization across a variety of available hardware, as well as other emerging architectures in the future."
— Dr. Manish Agarwal, Computer Services Centre, IIT Delhi
"We’re excited to be part of the oneAPI Beta evaluation to test the benefits of a unified software programming model across multiple types of hardware and accelerators. This project will help us explore diverse computing architectures for our AI research using a single development environment to optimize workloads and deploy more easily across a variety of hardware platforms."
— Rajat Subhra Chakraborty, PhD, associate professor, Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, West Bengal, India
"IIT supports the oneAPI concept for a single programming strategy that works across many types of architecture, as it will further extend our AI research conducted by our research scholars and masters students on different platforms. We are happy to participate in Intel’s oneAPI Beta evaluation and look forward to a fruitful research collaboration together."
— Dr. Durga Toshniwal, professor and researcher, Department of Computer Science and Engineering and head of the Centre for Transportation Systems, Indian Institute of Technology Roorkee
"Heterogenous computing is inevitable. It happens when a host schedules computational tasks to different processors and accelerators like CPUs and GPUs. This partnership will make scikit-learn* more performant and energy-efficient on multi-architecture systems.”
— Olivier Grisel, scikit-learn maintainer at Inria
Soda, a research team at Inria, announces Academic Centers of Excellence that improve the performance of the scikit-learn machine learning library: English
"High-performance computing (HPC) is the main solution for solving complex problems under the digital wave. Based on our shared vision for the future of computing, we are working together to solve computing challenges by collaborating with Intel on innovating open source software and other technologies. We will leverage our respective strengths to create new opportunities in open source software and power the digitalization revolution."
— Guangming Tan, director of the HPC Research Center in the Institute of Computing Technology, Chinese Academy of Sciences
"Interperformant Systems Ltd. was faced with a challenge: Our customer wanted to optimize a manually coded algorithm that had been working for years. We used Intel® VTune™ Profiler to quickly identify the problematic areas of the code. After vectorizing the code using Intel® Advanced Vector Extensions 512 (Intel® AVX-512), we used the Intel VTune Profiler feature, which allowed us to run tests on a repetitive algorithm on certain system loads with multiple targets. We determined which part of the code was consuming CPU time, were able to observe the underlying behavior of the microarchitecture, and ended up with a 30% overall speedup. If you want the best possible system performance, I highly recommend using Intel VTune Profiler."
— Dave Burley, director at Interperformant Systems Ltd.
Intensive debugging and successful benchmarking of the INTES FEM solver PERMAS (PERMAS is among the most advanced Finite Element Software Systems worldwide) with the new Intel LLVM* based Intel® Fortran Compiler, we decided to provide PERMAS also with the Intel Fortran Compiler compiled version as a commercial product. The most recent PERMAS application compiled with latest Intel Fortran Compiler version shows at par performance in comparison to the classical most recent Intel® Fortran Compiler Classic version. PERMAS also using Intel® Math Kernel Library (Intel® MKL), BLAS and LAPACK routine to boost its performance on Intel Xeon Platinum 8260L processor.
iOmniscient achieved 30% performance improvement for its iQ-series video application using Intel® VTune™ Profiler.
iOmniscient is one of the pioneers in video analytics with two decades of commercial experience. For our iQ-series video application, Intel Tune Profiler was helpful in identifying functions which were consuming more CPU time: for example, using Drawing Library from Windows*. We found decoding and encoding used separate sessions (synchronous mode), with no sharing of hardware resources for multiple transcoding applications. Thanks to Intel VTune Profiler, we followed asynchronous transcoding for multiple sessions, which not only helped to reduce compilation time by ~15% but also improved performance by 30% in terms of CPU and GPU usage in current video processing pipelines.
"As part of the Intel oneAPI startup program, Isima* used Intel® Developer Cloud to deploy bi(OS) on a three-node bare-metal system. This setup took 36 hours and operated for 20 days at 5 9’s reliability, simulating a real-time e-commerce recommendation engine. Based upon this achievement, e-commerce pioneers, such as PharmEasy, expect to save up to 60% on their data lakehouse TCO using Intel oneAPI Toolkits and Isima’s bi(OS)."
— Darshan Rawal, Founder and chief executive officer (CEO), Isima
"At Katana Graph*, we are building the best graph intelligence platform delivering highly scalable computations for machine learning and AI.
"I am proud of Katana Graph's partnership with Intel as we tackle the most challenging pain points of data scientists, enabling critical discoveries for data scientists to perform predictive analytics on massive datasets and to develop specific applications across a range of industries including financial services, life sciences, manufacturing, and security.
"A terrific example of our combined work is in the field of genomics where Katana Graph technology executed a 1.3 million cell genomic analysis on a next-gen Intel® Xeon® Scalable processor in 370 seconds, twice as fast as its closest competitor."
"With the help of Intel, we were able to train, optimize, and deploy a machine learning model in a lesser time and at a lower operational cost than available alternatives, enabling us to get to market fast with a powerful solutions that's optimized for Intel® architecture. Specifically, using OpenVINO™ toolkit from the Intel® oneAPI toolkits we were able reduce the model size which enabled us to deploy our solutions on edge devices."
— Ashok Ajad (technical lead, Medical Investment & Solutions)
"We’re excited to be working closely with Intel through their Intel® oneAPI tool Beta program. The vision of having a single unified programming model is a revolutionary approach that could fundamentally change how organizations deploy their workloads across a diverse set of accelerators and processors."
— Scott Tease, general manager, HPC & AI, Lenovo* Data Center Group
Lenovo Intelligent Computing Orchestration (LiCO) Is Now Powered by Intel® oneAPI HPC Toolkit and AI Tools
LiCO is Lenovo's one-stop software solution for HPC and AI. By integrating Intel® oneAPI toolkits, LiCO customers can significantly improve the performance of their HPC and AI applications on cross-architecture platforms. LiCO now contains the Intel® MPI Library to help end customers reduce network latency, increase throughput, and get better performance on HPC programs. For performance analysis, LiCO customers have access to Intel® Advisor, Intel® Trace Analyzer and Collector, and Intel® VTune™ Profiler to identify bottlenecks and allow optimizations. Intel® Extension for TensorFlow* and Intel® Extension for PyTorch* accelerate AI programs on Intel CPUs and GPUs. Finally, the Intel® Neural Compressor can reduce complex AI models, producing smaller, faster models without losing accuracy.
"Establishing the oneAPI Center of Excellence enhances the scientific expertise of UNN and allows us to solve more complex research problems in classical and quantum systems utilizing the power of multiple architectures. Furthermore, the educational activity of the Center will strengthen our standing in the field of education in Russia."
— Mikhail Ivanchenko, professor, UNN’s vice rector for research
"MATLAB* and Simulink* users design large systems with multidomain components that increasingly rely on AI. Whether running simulations on a host machine or deploying to the cloud or edge, AI performance is critical. Using Intel® oneAPI Deep Neural Network Library (oneDNN) enables our solution to provide best-in-class performance on Intel platforms."
“We are always looking for new methods to accelerate workloads in our data center. Our teams used Intel® VTune™ Profiler’s flame graph feature and found it intuitive to use and practical for interpreting performance data. This tool [part of the Intel® oneAPI Base Toolkit] has become essential to optimizing code and workflows, and its ability to work across Intel CPUs and GPUs adds to our productivity and performance optimization efforts."
— Dr. Markus Rampp, head of HPC Applications division and deputy director, Max Planck Computing & Data Facility
Intel® Fortran Compiler Allowed Us to Seamlessly Incorporate GPU Computing into Our CPU Workflow
Intel® Fortran Compiler easily allows running code on GPUs. It allowed us to experiment with porting the main hot spot of our GRILLIX 3D turbulence simulation to Fortran with OpenMP* offloading. This version runs out of the box on an Intel® Data Center GPU server and even in its early stages showed performance improvements when comparing CPUs and GPU versions. In this small benchmark, the Intel® Data Center GPU Max Series reduced the out-of-the-box computation time to 40 percent when compared to 4th gen Intel® Xeon® processors.
This is especially valuable as Intel Fortran Compiler supports not only the GPU offloading features, but is also fully compliant with the latest Fortran 2018 standards. This collaboration with Intel showed us a promising path for the future of the porting of the code to GPUs.
"Mediakind* is a global leader in media technology and services. Its Emmy* award-winning Aquila headend solution enables broadcasters, operators, and service providers to efficiently and reliably distribute and deliver live and on-demand video content to the viewer. The runtime performance of this software is essential for real-time delivery and cost effectiveness.
"Thanks to the Intel® oneAPI DPC++/C++ Compiler, the core of Aquila Live software now not only runs 5%-10% faster but also the compilation time is reduced by 30% vs. Intel® C++ Compiler Classic. This is a significant performance boost for content processing software which leverages decades of video compression knowledge and experience."
"Complex workloads today demand more efficient development strategies to deploy them across many types of architecture. Megh Computing is delighted to see oneAPI as an open project with a single programming approach that works across different processors and accelerators. We are pleased to collaborate with Intel and the ecosystem on oneAPI, and excited to test the model across the Intel® FPGA Programmable Acceleration Cards, CPUs, and future discrete GPUs in our early projects with the goal to ultimately take them to market."
"In [high-performance computing] HPC, different hardware vendors require proprietary programming models which slows down developer productivity. MEGWARE Computer is proud to support Intel’s vision of a unified programming model for developing applications across a variety of hardware. With oneAPI, HPC developers can focus their cycles on addressing large computational problems efficiently rather than coding for disparate hardware environments."
— Axel Auweter, chief technology officer (CTO), MEGWARE GmbH
"Intel® oneAPI toolkits helped increase our end-to-end application processing performance on Intel® Xeon® platforms. By using oneAPI technology including Intel® Integrated Performance Primitives (Intel® IPP), which is a set of high-performance software library combined with hardware deep optimization providing a large number of signal processing, image processing and other functions, we were able to significantly improve our image-processing code performance by 2.7x in image rotation, and 4x in image resize. This allows us to analyze larger image datasets, and builds the cutting-edge visual AI Inference solution for our end customers."
"Intel and Mercenaries Engineering are partnering to achieve fast-paced 3D production rendering powered by innovative technology. Guerilla Render / Guerilla Station integrate Intel® Open Image Denoise, a CPU-based open, high-performance, easy-to-use denoising filter solution. The technology is part of the Intel® Rendering Framework that makes use of artificial intelligence to remove noise and significantly reduce the rendering times of production-quality images. Guerilla Station and Guerilla Render is a production-proven look development, assembly, lighting and rendering solution designed for the animation and VFX industries. Used on a wide range of productions, from full CG to hybrid and VFX, from feature films to series, Guerilla is the state of the art software, easy to use and to deploy in pipelines, and gives all the flexibility needed by productions, with no compromise on performances."
"The industry needs a programming model where developers can take advantage of an array of innovative hardware architectures. The goal of oneAPI is to provide increased choice of hardware vendors, processor architectures, and faster support of next-generation accelerators. Microsoft* has been using oneAPI elements across Intel® hardware offerings as part of its initiatives and supports the open standards-based specification. We are excited to support our customers with choice and accelerate the growth of AI and machine learning."
"LNCC is participating in Intel’s oneAPI Beta and welcomes the open approach from Intel to drive industry innovation more rapidly in the heterogeneous computing for field of high-performance computing (HPC). We are pleased to collaborate with Intel and contribute to the HPC community with our inputs to this new and open programming model being designed to support a diverse mix of accelerators."
— Wagner Vieira Leo, Coordinator of IT and Communications, LNCC
Netflix* used Intel® oneAPI Deep Neural Network Library (oneDNN) to reduce latency on their FFmpeg*-based filter, which runs with other video transformations, like pixel format conversions. They also used Intel® VTune™ Profiler to uncover performance issues caused by the migration of workloads to a larger cloud instance, resulting in 3.5x performance improvement. To learn more, see:
"The ddiLab at Northern Illinois University is excited to be named a oneAPI Center of Excellence allowing our students to learn and develop software capable of running on some of the largest and fastest machines in the world, such as Argonne National Laboratory’s Aurora super computer."
— Michael Papka, presidential research, scholarship, and artistry (PRSA) professor of computer science
"This work [oneAPI Center of Excellence] helps us advance scientific visualization, along with venture into new areas and usages."
—Joseph Insley, associate research professor in the School of Art and Design
"SYCLomatic helped us quickly move the CUDA*-optimized numerical integration code to Intel oneAPI and SYCL*. The SYCL version gave us portability, and we could run the code on Intel® GPUs and CPUs, and NVIDIA* GPUs. We demonstrated that the SYCL code provided 90% of the performance as a CUDA-optimized code on NVIDIA V100."
oneAPI helps get the most out of the latest Intel® Xeon® CPU Max Series processors that are equipped with high-bandwidth memory (HBM). A range of data-intensive applications show speedups of 2.3 to 4.3x compared to the previous generation of CPUs, putting all the extra bandwidth to good use. What’s more, the same code is portable to the latest Intel, AMD*, and NVIDIA* GPUs.
"Peraton Labs generates transformative applied research to fuel solutions for our customers’ most difficult challenges. We’re an innovation engine at Peraton, delivering trusted and highly differentiated national security solutions and technologies that keep people safe and secure. Peraton’s Cross-domain Language-extensions for Optimal SecUre Refactoring and Execution (CLOSURE) toolchain enables software engineers to easily build cross-domain applications with provably secure architectures. Such applications isolate and protect against high-risk transactions, meeting critical needs in defense and intelligence. Intel® oneAPI HPC Toolkit (HPC Kit) allows users to build, analyze, and scale applications across shared- and distributed-memory computing systems. Peraton is collaborating with Intel to combine CLOSURE with the HPC Kit. The resulting solution jointly addresses cross-domain application partitioning and HPC concerns, filling an important gap in Department of Defense and Intelligence Community tooling."
"Based on our current experience using Intel® software, having oneAPI as a unified software stack that works across several hardware solutions is a great concept. Given today’s programming challenges deploying solutions on different platforms, oneAPI seems to be a perfect match to streamline development efficiency."
— Ishai Tal, head of Platform and Cloud Architecture, Philips Algotec
QCT's oneAPI DevCloud migrates from being an enterprise on-premises cloud solution provider to an OpenLab concept in 2022 after demonstrating the capability to fine-tune performance-optimized results for several HPC workloads such as NWP and molecular dynamics using the Intel® oneAPI Base & HPC toolkits. The OpenLab project phase will focus on validating heavier HPC and AI workloads such as OpenFOAM, VASP, AI Reference Kits from Intel, etc. for organizations like government entities and academic science research centers. With Intel® oneAPI Base, HPC & AI Analytics Toolkits, QCT oneAPI DevCloud users can profile and optimize their code to its fullest potential on cross-architecture converged HPC and AI platforms. oneAPI not only helps developers to increase performance and productivity but also lowers their development costs by facilitating code reuse and reducing time spent reprogramming.
"We believe the future of AI is open, it is hybrid, and it will extend to the edge. Red Hat* and Intel are committed to giving AI developers what they need to prepare for this future. We worked with Intel to help them create the Intel® AI Developer Program to give developers learning materials and experience with Red Hat OpenShift* Data Science and Intel® AI software suite to accelerate the building and deploying of intelligent applications to edge environments."
— Steven Huels, senior director, AI Services, Red Hat
"To manage the rapid growth of data and scale infrastructure efficiently, customers are adopting heterogeneous platforms. Our solution is built on such a platform [that uniquely leverages] FPGAs and CPUs. The oneAPI programming model will enable more efficient development resulting in faster time to market, and [will] ultimately help us meet our customers’ needs quickly. We look forward to working with Intel and other ecosystem partners to bring more innovative solutions to market supporting different hardware architectures using this set of common programming APIs."
“We are integrating Samsung’s image processing technology, semiconductors, ergonomic mechanics and… AI technology into our ultrasound systems for efficient and confident diagnosis. One tool…to accelerate for pursuing this effort more efficiently and with flexibility is Intel’s oneAPI solution. Samsung Medison is working on a medical imaging proof of concept using oneAPI to write one source code implementation for performance acceleration on different kinds of hardware... The Intel® DPC++ Compatibility Tool made it easy to port our existing code to DPC++ and Intel’s training… and technical resources helped us use Intel® VTune™ Profiler to analyze code performance and further enhance it to run optimally on our products. We look forward to our continued collaboration with Intel as using the oneAPI solution will allow us to respond quickly to new requests from our healthcare professionals.”
— Won-Chul Bang, PhD, vice president and head of product strategy, Samsung Medison
The suite of tools available in Intel oneAPI has become an integral part of software development process at SankhyaSutra Labs. From developing optimized products using the Intel® C++ Compiler, Intel® Math Kernel Library, Intel® oneAPI Deep Neural Network Library (oneDNN), and identifying performance gaps using APS to leveraging the DPC++ programming model for heterogeneous HPC systems, the entire workflow is available in one place as part of the Intel® oneAPI toolkits. This has eased development efforts and allowed more time to focus on the business case of providing fast and scalable engineering simulation software.
"Intel oneAPI has helped us integrate our HPC software development, profiling and deployment into a seamless workflow."
— Soumyadeep Bhattacharya
"The Intel® oneAPI toolkits provide a tremendous boost to simulation software development workflows with increased ease of access to Intel's high performance optimizations in Intel® C++ Compiler, Intel® MPI Library, and profiling tools; introduction of DPC++ for programming on heterogeneous systems with GPUs and FPGAs; and visualization of large data sets using optimized rendering libraries."
"SAP* welcomes Intel’s strategy to offer a unified programming model (oneAPI) based on an open specification, which is designed to provide a higher abstraction for parallel language support (in DPC++) to seamlessly program current and future heterogeneous architectures. Based on a programming model [that's] familiar to developers (C++), DPC++ has the potential to enable the vast majority of the SAP HANA* C++ developers to efficiently get full performance out of diverse hardware platforms running in-memory databases like SAP HANA."
— Dirk Basenach, head of database, SAP HANA and Analytics, SAP
"With today’s data management challenges, the industry needs a unified solution for native programming of CPUs and accelerators for efficient cross-architecture development. The oneAPI initiative with its open specification and industry standards will do much to push an ecosystem-wide solution forward. SAS* and Intel have a rich history to drive innovation in the market. We are pleased to work with Intel to evaluate oneAPI and its Beta tools, [and deliver] breakthrough innovation for our customers."
— Bryan Harris, senior vice president of R&D Engineering, SAS
"Heterogeneous programming for multiple platforms (CPUs, GPUs, FPGAs, and AI accelerators) is a challenge for us and also for the industry. SENAI-CIMATEC is glad to collaborate with Intel on the oneAPI Beta program and look forward to providing feedback on this open, unified software stack targeted to simplify programming across different compute engines for a variety of [high-performance computing] HPC workloads."
“As networks increase in complexity, testing is becoming even more important. Intel® oneAPI toolkits help Spirent stay ahead of the latest technologies and network speeds. Leveraging tools like Intel® VTune™ Profiler and Intel® compilers help us better understand where we need optimization and offer tools for improving performance for both embedded and cloud systems. This in turn enables our customers to test and verify their networks and infrastructure effectively and with confidence using Spirent test solutions.”
— Matthew Philpott, principal architect, Spirent Communications
"As the leader of the GROMACS development team (one of the most widely used [high-performance computing] HPC codes in the world for molecular simulations) at Stockholm University and KTH, I’m delighted to strongly endorse Data Parallel C++, a cross-architecture development language, based on the first specification and road map. We think it's outstanding to finally see a strong C++ enabled accelerator development environment, as well as the strong commitment to an open project and industry specifications. Furthermore, the aim of contributing parallel and accelerator-enabled functionality as part of future C++ standards is just as important, since this will be a revolution for portability."
“With GROMACS 2022’s full support of SYCL* and oneAPI, we extended GROMACS to run on new classes of hardware. We’re already running production simulations on current Intel Xe architecture-based GPUs as well as the upcoming Intel Xe architecture-based GPU development platform Ponte Vecchio via the Intel® Developer Cloud. Performance results at this stage are impressive–a testament to the power of Intel hardware and software working together. Overall, these optimizations enable diversity in hardware, provide high-end performance, and drive competition and innovation so that we can do science faster, and lower costs downstream.”
— Erik Lindahl, biophysics professor, GROMACS development team, Stockholm University and KTH
"SUSE* is the most customer-centric open source company in the world, and that’s why we look forward to the oneAPI initiative. Its goal of delivering a single multi-architecture programming environment based on an open specification and industry standards will benefit enterprise users globally. SUSE anticipates ongoing collaboration with Intel around this initiative as well as others, in order to help ease software development and deployment for our joint customer base."
"As workloads and available hardware choices diversify, software developers want to choose hardware that addresses unique requirements of every workload without adding complexity to their software workstreams. We’re excited to work with Intel on the oneAPI initiative, a new and open programming model that aims to reduce that complexity for our developers."
— Ariel Pisetzky, vice president, Information Technology and Cyber, Taboola*
"Tech Mahindra continues to build its strategic partnership with Intel. We are pleased to collaborate on the open project, oneAPI, which promises to truly usher in an era of heterogeneous computing. With our large global customer base (including Fortune 500 companies), we are poised to unlock new opportunities through oneAPI in the industries using diverse workloads. Use of Intel® FPGA Programmable Acceleration Cards, Intel® GPUs, and Intel® CPUs will bring in additional benefits and drive growth to our customers. We are excited with this game-changing moment and happy to be part of this journey!"
— Pritam Parvatkar, senior vice president and global head, Strategic Technology Business, Tech Mahindra
“We are excited to join the circle of other top research institutions as a newly established Intel oneAPI Center of Excellence. We look forward to collaborate with Intel’s experts to apply the huge strides oneAPI has made over other programming models to realize better and faster docking simulation tools, with the potential to scale from individual researcher’s workstations up to supercomputers.”
— Professor Andreas Koch, principal investigator at the Intel oneAPI Center of Excellence at Technical University of Darmstadt
Technical University of Darmstadt Establishes Intel oneAPI Center of Excellence: English
“We are excited to establish the new oneAPI Center of Excellence with Intel. As heterogeneous supercomputers worldwide are on the rise, and diverse high-performance computing is practically ubiquitous, there is a need to raise a new generation of developers who can push legacy and new-generation applications performance to the limit. With oneAPI, we can close the gap between software and hardware and exploit the full potential of both. The future, in this regard, is here, and we are planning to seize the moment.”
— Dr. Gal Oren, oneAPI Center of Excellence lead, Technion Computer Science Department
Intel oneAPI Center of Excellence at the Technion - English | Hebrew
"We welcome how Intel is driving oneAPI as an open industry initiative to foster hardware and software ecosystem innovation and adoption. We look forward to participating in the initiative and are evaluating Intel® oneAPI tools for our cross-architecture programming needs. This initiative represents an excellent opportunity to create a new unified experience for our developer community through Tencent Cloud."
— Zhang Wenjie, general manager, AI Platform and IoT Products, Tencent Cloud
"TencentDB for MySQL* is designed to provide customers with secure, reliable, high-performance, and easy-to-maintain enterprise-level cloud database services. And Intel® oneAPI DPC++/C++ Compiler can bring Tencent another avenue to get better MySQL performance."
"With the growth of AI, machine learning, and data-centric applications, the industry needs a programming model that allows developers to take advantage of rapid innovation in processor architectures. TensorFlow supports the oneAPI industry initiative and its standards-based open specification. oneAPI complements TensorFlow’s modular design and provides increased choice of hardware vendor and processor architecture, and faster support of next-generation accelerators. TensorFlow uses oneAPI today on Xeon processors and we look forward to using oneAPI to run on future Intel architectures."
"Intel has been a strong partner with TACC and an innovator in visual analysis techniques to unlock the mysteries of science at the largest scales. We're thrilled to continue working with Intel and the talented teams across the oneAPI ecosystem to advance capabilities to find solutions to today's and tomorrow's problems, and effectively communicate those findings to our stakeholders and communities."
— Paul Navrátil, TACC's director of Visualization and Intel Graphics Visualization Institute, and Intel oneAPI Center of Excellence
"We regularly use the Intel® Compiler as our default on all the Intel chips because we get consistent and repeatable performance. We rely super heavily on VTune and some of the other Intel products that are our primary way to understand performance at very large scale."
"Doing a project like this reinforces that there’s a process to learning. You have to measure, experiment, and repeat. You need to be able to visualize the changes you’re making.[Intel® VTune™ Profiler] was great for that. You need to challenge assumptions. We did not walk into this project expecting that we could reduce the disk count by 75%. And as you get data from each experiment, refine what you’re doing and try again."
— Matt Singer (@mattbytes), server hardware architect
"The Intel DPC++ Compatibility Tool interoperability with Microsoft Visual Studio* IDE helped to seamlessly migrate CUDA code to DPC++. The Intel® oneAPI DPC++ Compiler, Intel® Integrated Performance Primitives (IPP), the Intel® oneAPI Math Kernel Library (oneMKL), and the Intel® VTune™ Profiler from the Intel® oneAPI Base Toolkit and Intel® oneAPI IoT Toolkit are all critical to our product line."
— Tian Wang, R&D manager, United Imaging Healthcare & Magnetic Resonance Software
"To achieve high hardware interoperability of HiperBio codes, oneAPI and DPC++ has been used to implement cross-device and efficient epistasis detection (bioinformatics) software. When compared with state-of-the-art C++ fourth-order approaches targeting modern CPU, our epistasis detection software based on DPC++ is 33% faster on CPU, while also unlocking close to 10× higher performance on an Intel® Iris® Xe MAX GPU running exactly the same DPC++ code."
— Aleksandar Ilic, assistant professor, Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento em Lisboa (INESC-ID), Instituto Superior Técnico (IST), University of Lisbon, Portugal
"We compared the TBB+OpenCL versus the oneTBB+oneAPI implementations of our heterogeneous schedulers, observing that oneAPI versions result in up to five times less programming effort and only incur in 3% – 8% of overhead." †
"The Application Performance Snapshot feature of Intel® VTune™ Profiler helped us analyze HemeLB running at 96K MPI ranks on SuperMUC-NG of the Leibniz Supercomputing Centre. It was straightforward and effective in its operation and analysis output.”
"The SYCL parallel programming model enables performance portability, however achieving this in practice is not always easy. Becoming a oneAPI Center of Excellence will allow us to share our expert knowledge of SYCL and performance portability, and enable developers to write fast HPC applications more productively on CPUs and GPUs."
– Dr. Tom Deakin, Bristol’s principal investigator and lecturer in Advanced Computer Systems
"This new partnership builds on our long-standing collaboration with Intel. Our research group is a world-leader in finding solutions to enable scientific codes to be performance portable across the most advanced hardware, and we see oneAPI as a vital piece of this puzzle."
– Professor Simon McIntosh-Smith, head of the HPC Research Group in Bristol
"It’s great that Intel is playing a leadership role in the development of oneAPI, a much-needed standard to enable smooth deployment across diverse computational platforms. Our center will use oneAPI to enable the easy migration of natural language and recommendation system workloads."
– Kurt Keutzer, professor
"Transitioning to oneAPI will significantly reduce the overhead of porting from one platform to another, which is a challenge of proprietary programming approaches and will enable greater innovation in both hardware and software systems for machine learning."
"The UC Davis team is committed to developing high-performance visualization software solutions through the use of oneAPI technologies and educating best practices to both the visualization research and scientific user communities."
— Kwan-Liu Ma, distinguished professor of computer science
UC San Diego oneAPI Center of Excellence to Bring High-performance Simulations to Amber
"We want to push the boundaries of science to gain insights that are out of reach today. It is thus exceptionally critical for us to achieve the highest possible computational performance on any given hardware and to be able to use all the fastest supercomputers in the world, including new exascale machines in multiarchitecture systems including the latest CPUs and GPUs."
— Andreas Goetz, assistant research scientist at San Diego Supercomputer Center and group leader for Data-Driven and High-Performance Computational Chemistry, UC San Diego
"Owing to algorithmic advances and hardware breakthroughs, we have come a very long way in simulation of biological systems and processes highly relevant to human health and disease. The expectation from simulation engines like NAMD is to provide molecular insight, which cannot be obtained otherwise, into key mechanisms and details that can be harvested to address major concerns in human health, as clearly exemplified by the current work performed at many labs on COVID-19 virus. A key element in our successful simulation of biological systems has been longer and faster simulations, achieved by maximal exploitation of available hardware technology in the best way possible, which also constitutes the main goal of the UIUC oneAPI CoE."
— Emad Tajkhorshid, director of NIH Center for Macromolecular Modeling and Bioinformatics, and Theoretical and Computational Biophysics Group at Illinois, the creator of NAMD and VMD
"With the advancement of multicore processor and GPU architectures and their realization in next-generation products comes the key need for tools that can identify areas for tuning for maximum performance. The TAU project at the University of Oregon is pleased to announce support for the Intel Xeon and Xe platforms in the TAU Performance System*.”
— Sameer Shende, director of the Performance Research Lab, NIC, University of Oregon
"The international network of Intel and its academic partners is extremely valuable for the exchange of expertise. It also gives us access to various deployed platforms for developing and testing our framework and visualization approaches, such as the Texas Advanced Computing Center, which provides friendly, no-fuss support and ample testing opportunities. We are continuously extending our collaborations with other institutions to funnel expertise into developing novel and useful features in our framework. Together, these motivated teams push the envelope of technical capabilities and visualization all the time."
— Dr. Guido Reina, research associate and MegaMol development lead
"Numerical libraries like BLAS and LAPACK have been the major building blocks for many scientific computing applications–the portability of BLAS and LAPACK implementations as in the MAGMA library has enabled the portability of countless applications. Results show that Intel’s oneAPI tools can be used not only to quickly migrate MAGMA’s GPU algorithms and CUDA codes to DPC++/SYCL* using Intel® DPC++ Compatibility Tool but also that the resulting oneAPI MAGMA can be easily autotuned for performance portability across vendor GPUs and multicore CPUs."
— Stanimire Tomov, Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville
"Intel is an internationally recognized leader in the computing industry, and the establishment of this center is a great indication of the global impact of the tremendous HPC work being done here, with 35 ongoing projects in numerical linear algebra, performance evaluation and benchmarking, and distributed computing just in the ICL alone. We’re excited about this opportunity and eager to see the innovations that it helps develop."
— Matthew Mench, dean of Tickle College of Engineering, and Wayne T. Davis Dean’s chair
"The university is delighted to work with Intel in developing this open-innovation platform. We know it will unleash the development of a wide range of applications, products, and services that will simultaneously advance science, innovation, and discovery, while also enhancing the health, wealth, and prosperity of communities here in Tennessee and around the world."
—Deborah Crawford, vice chancellor for research, University of Tennessee
"We completed the full software portability of Ginkgo on oneAPI (CUDA* to SYCL*) with an optimized SYCL back end enabling the deployment of hardware-optimized kernels on any GPUs. This fully validated functional port of Ginkgo also enables domain scientists to run high-performance scientific simulations on any GPUs including Intel’s MAX Series."
— Dr. Hartwig Anzt, UTK oneAPI Center of Excellence, PI
"The SCI Institute's pioneering research in visualization, imaging, and scientific computing and its long track record in creating open source scientific software will enable their work on oneAPI to help scientists, engineers and biomedical researchers to focus on their research instead of the details of the underlying software."
— Dan Reed, senior vice president of Academic Affairs, University of Utah
"The University of Utah’s [Center for Extreme Data Management Analysis and Visualization] CEDMAV, in collaboration with and LLNL’s [Center for Applied Scientific Computing] CASC have been pioneering research in managing extreme data applications involving scientific simulations and experimental facilities. This collaboration has a long track record of developing and deploying open source scientific software that finds broad adoption in the communities of interest. This oneAPI Center of Excellence will strengthen this collaboration and help this academic research find practical adoption on multiarchitecture systems."
— Manish Prashar, director of the Scientific Computing and Imaging Institute, University of Utah
"Ensuring the best possible performance of systems for our users is a top priority for us. Intel VTune Profiler helps us do that with effective workload management. It gives us abstracted information with the ability to dive deeply with details such as hotspots, cache miss ratios, amount of concurrency, and lock contention mapped to function, source code line, and assembly instruction. By identifying issues that were otherwise overlooked, it allowed us to improve the performance of some of our crucial and revenue-impacting applications. Our team team helps save the company tens of millions of dollars by using features like the Platform Profiler to manage performance issues on our servers and get useful insights into how we can achieve the highest levels of performance from our hardware."
— Dennis O'Connell, senior director of performance engineering, Verizon*
"VMware* is excited to announce that in collaboration with Intel we are providing media acceleration via AV1 encoding and decoding on Intel® Arc™ graphics and Intel® Data Center GPU Flex Series optimized by the Intel® oneAPI Video Processing Library (oneVPL). Enabled through oneVPL, Blast will deliver fast hardware encoding and decoding on Intel® GPUs using the AV1 codec."
"Federated learning open source framework is designed to help users build federated modeling solutions more efficiently and quickly, to create better performing AI models, using rich multi-source data. The modular exponentiation operation of partial homomorphic encryption in our FATE (Federated AI Technology Enabler) framework has been enhanced significantly through the introduction of the multi-buffer function provided by Intel® Integrated Performance Primitives Cryptography library, helping improve the overall efficiency of user scenarios as well as reducing TCO."
— Qian Xu, vice general manager of the AI department, WeBank*
"We are pleased to see the SYCL* standard used as the foundation of oneAPI. This drives the collaboration on open source implementations including up-streaming to Clang/LLVM* and motivates further community input to the standards body at Khronos* SYCL."
— Ronan Keryell, editor for the Khronos SYCL standard, and principal software engineer, Xilinx Research Labs
"Intel® oneAPI toolkit has become an integral part of our software development process at YUAN High-Tech. We developed optimized video processing platform using the Intel® Core™ processors and the OpenVINO™ toolkit. After optimization, most of the AI algorithms achieved a performance improvement of around 4-5x. It can help partners develop innovated smart video solutions and provide greater insights from video data."
"Increasing the performance of diverse demanding workloads on a wide range of platforms with CPUs and accelerators (GPUs and FPGAs) while maintaining the energy envelope is critical for larger compute systems like the [North-German Supercomputing Alliance] HLRN installation at the Zuse Institute Berlin. We are participating in the Intel oneAPI Beta program to evaluate solutions leveraging a single cross-architecture programming model that will enable performance, increase productivity, and reduce costs. With oneAPI, our [high-performance computing] HPC and data analytics community has a path to a near-future software ecosystem that can more easily support heterogeneous platforms built on CPUs and accelerators."
— Dr. Thomas Steinke, head of the Supercomputing Department, Zuse Institute Berlin
"The Intel® DPC++ Compatibility Tool greatly supported our porting efforts to create a single source DPC++ version of the tsunami simulation EasyWave and to shift away from individual source codes for CPUs (OpenMP*) and GPUs (CUDA*). The obtained code from the automatic conversion provided a solid ground and required only minor adjustments to get a working DPC++ version of the application. We also appreciate the promising performance characteristics of easyWave with the early, pre-product oneAPI releases."
— Dr. Steffen Christgau, research associate, Zuse Institute Berlin
These organizations support the oneAPI initiative concept for a single, unified programming model for cross-architecture development. It does not indicate any agreement to purchase or use Intel’s products.
†Intel does not control or audit third-party data. You should consult other sources to evaluate accuracy.
††Up to 90% Memory Reduction for Displacement
Testing conducted by Chaos Group with Intel® Embree
Software: Corona Renderer 5 with Intel® Embree
‘Up to 90% memory reduction’ calculated using Corona Renderer 5 with regular displacement grids per triangle of 154 bytes versus Corona Renderer 5 with Intel® Embree, which has a displacement capability grid of 12 bytes per grid per triangle. (12/154 = 7.8% usage or >90% memory reduction).
Recreation of the performance numbers can be accomplished using Corona Renderer 5 and Intel Embree.
For more information, visit the Corona Renderer Blog.
††† Intel configuration: CPU and GPU on Intel® Developer Cloud: Intel® i9-9900K + DG1 (NDA) and Intel® Xeon® E-2176G + P630 (Gen9.5), optimized by Intel® oneAPI Tools Beta 8.
‡‡8x improvement was achieved on Intel® Xeon® Gold 6230 and Xeon® Platinum 8280 processors, based on single AI Computer Vision model (Resnet50).
‡‡‡ Testing Date: Results are based on data conducted by Cinesite 2020-21. 10% to up to 25% rendering efficiency/thousands of hours saved in rendering production time/15 hours per frame per shot to 12 to 13 hours. Cinesite Configuration: 18-core Intel® Xeon® Scalable processors (W-2295) used in render farm, 2nd gen Intel® Xeon® processor-based workstations (W-2135 and -2195) used. Rendering tools: Gaffer, Arnold, along with optimizations by Intel® Open Image Denoise.