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When performing the MAXLOC operation, should you use SYCL* reduction or oneDPL? This article answers that valid programming question.
Using the standards-based oneDPL significantly reduces heterogeneous programming efforts and improves performance.
Learn two approaches for migrating a linear algebra Jacobi iterative method written in CUDA* to the SYCL heterogeneous programming language.
Get a hands-on look at using the this component to compile SYCL code built for cross-architecture deployment.
An Intel solution won the NeurIPS Billion-Scale Approximate Nearest Neighbor Search Challenge, improving total cost of ownership by up to 19.7x over the solution from NVIDIA*.
Transform cross-platform debugging challenges into streamlined efficiency and effectiveness with the Intel® Distribution for GDB*.
Get the steps to debug your SYCL and OpenCL™ applications across CPUs, GPUs, and FPGAs.
Linux* Host | Windows* Host
Get a better workflow for performance profiling or accessing performance data for scheduled jobs in computing clusters.
Support for core tools and libraries to build and deploy high-performance data-centric applications
Support for Intel® oneAPI DPC++ Compiler, oneDPL, Intel® DPC++ Compatibility Tool, and GDB*
Support for Intel® VTune™ Profiler, Intel® Advisor, Intel® Inspector
Build applications that can scale for the future with optimized code designed for Intel® Xeon® and compatible processors
Gradient boosting is a powerful technique for building predictive models, but it has challenges. XGBoost, optimized by Intel, removes them.
The CTO of Ponder*—the company behind Modin*—discusses how the drop-in pandas replacement helps data scientists handle large datasets with ease.
Speed up deep-learning workloads on Intel® CPUs and GPUs using Model Zoo’s optimized inference applications and the Intel® Extension for TensorFlow*.
Accelerate deep-learning applications—natural language processing (NLP), recommender systems, computer vision—on Intel CPUs and GPUs with Intel® Extension for PyTorch*.
Intel and other industry leaders are using advanced ray tracing to deliver an open and accessible metaverse of photo-realistic digital experiences.
A research engineering scientist from Texas Advanced Computing Center (TACC) discusses scientific visualization for rhinoviruses, oceanography, plasma structures, and more.
Learn how movie studio Laika* reduced training time by nearly 87%—from 23 hours to less than three—using the Intel® oneAPI AI Analytics Toolkit, as measured on Amazon Web Services (AWS).
The low-level volumetric data-processing algorithms of Intel® Open Volume Kernel Library can streamline the rendering and simulation processing of 3D spatial data.
Explore hundreds of applications that take advantage of elements of the Intel oneAPI cross-architecture programming model.
See the ecosystem support for oneAPI from a growing, global list of companies, universities, and institutions.
Find answers to technical questions, plus links to community and priority support and forums for Intel oneAPI Toolkits and individual tools.
See the growing collection of heterogeneous-distributed applications your peers and colleagues are creating using Intel oneAPI tools.
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