NVIDIA Recognizes Chinese Academy of Sciences and Tsinghua University as CUDA Centers of Excellence

NVIDIA Recognizes Chinese Academy of Sciences and Tsinghua University as CUDA Centers of Excellence

Leaders in Chinese Educational and Research Community Join List of Five Other Elite Universities Around the World as Pioneers of GPU Computing

BEIJING, China -Oct. 28, 2009-NVIDIA today announced that the Institute of Process Engineering (IPE) at the Chinese Academy of Sciences (CAS) and Tsinghua University have been recognized as CUDA Centers of Excellence for their commitment to furthering GPU Computing research and their teaching of parallel programming courses based on the CUDA™ architecture.

They join an elite list of five other universities as CUDA Centers of Excellence, including: Harvard University, University of Illinois at Urbana-Champaign and University of Utah, in the U.S.; Cambridge University, in the UK; and National Taiwan University, in Taiwan. Additionally, more than 250 other universities around the world teach the CUDA C programming model.

NVIDIA's recognition of the CAS IPE and Tsinghua University stems, in part, from the institutions having demonstrated their commitment to revolutionizing science and engineering research with GPU Computing by leveraging NVIDIA® Tesla™ GPUs across a host of science and engineering research projects.

Established in 1958 as China's premier research institution, CAS leverages high performance computing (HPC) technology to conduct research that spans many fields including chemical engineering, oil and gas, sustainable technologies and molecular dynamics.

"The establishment of the IPE-led CUDA Center of Excellence at CAS will provide a strategic opportunity for both China and NVIDIA to take a leading role in application-oriented HPC at a critical turning point for both computing technology and process engineering," said Li Jinghai, vice president of CAS. "Using the GPU-CPU co-processing model, the IPE has achieved great results in complicated problems such as multiple-phase reactor designs, micro-nano systems modeling and secondary and tertiary oil recovery. We believe that this emerging model will be the promising way to go for China's supercomputing industry."

Established in 1911, Tsinghua University is the most prestigious technical university in China and one of the top technical universities in the world. Tsinghua University is a national leader in promoting parallel programming on the CUDA architecture with several classes being taught to many hundreds of student developers.

"Tsinghua University has been taking advantage of the CUDA C programming model since its introduction, as we quickly realized the benefits that GPU Computing brings to many areas of our research," said Prof. Chen Wenguang, Institute of HPC, at Tsinghua University. "Co-processing with a GPU and CPU has opened up a new world of possibilities with regards to accelerating our research and providing our students with a solid grounding in parallel programming education. Students that go through the Tsinghua CUDA Center of Excellence will be the developer superstars of tomorrow."

"We are truly honored to recognize CAS and Tsinghua University as CUDA Centers of Excellence for their excellence in both parallel computing education and scientific research," said Bill Dally, chief scientist at NVIDIA. "Our NVResearch group looks forward to working with their teams to further advance the field of GPU Computing."


About NVIDIA

NVIDIA (Nasdaq: NVDA) awakened the world to the power of computer graphics when it invented the graphics processing unit (GPU) in 1999. Since then, it has consistently set new standards in visual computing with breathtaking, interactive graphics available on devices ranging from portable media players to notebooks to workstations. NVIDIA's expertise in programmable GPUs has led to breakthroughs in parallel processing which make supercomputing inexpensive and widely accessible. Fortune magazine has ranked NVIDIA #1 in innovation in the semiconductor industry for two years in a row. For more information, see www.nvidia.com.

Last updated: Apr 7, 2020 at 12:00 pm CDT