Great Cross-Architecture Challenge Showcase: Zhen Ju

Zhen Ju of China, a challenge participant winner, demonstrates the migration of a CUDA-based application and the benefits of an open programming model for all architectures. The ported application offers a more efficient and accurate solution to filter out redundant sequences in genetic data.

The Great Cross-Architecture Challenge was a 14-week contest for professional and student software developers who are interested in developing cross-architecture applications using oneAPI. Participants were challenged to be the next “oneAPI hero” by either porting an existing C/C++ or CUDA application using the Intel® DPC++ Compatibility Tool or by creating an entirely new oneAPI application. As part of the contest, developers received free access to Intel® oneAPI Toolkits on Intel® DevCloud across an array of Intel CPUs, GPUs and FPGA architectures, along with resources such as code samples, dev guides, webinars, and a developer collaboration portal (Intel® DevMesh).

 

Speaker

Zhen Ju earned his master's degree from the University of the Chinese Academy of Sciences (UCAS) in 2016, and now is a PhD candidate at UCAS majoring in computer science. His research focuses on the fields of high-performance computing and heterogeneous acceleration. He has experience in accelerating codes on heterogeneous devices. He has developed an application that can remove redundancy sequences from biological sequences by CUDA and migrate it to oneAPI.

Product and Performance Information

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