A six-person team from Nanyang Technological University (NTU) has achieved 56.51 teraflops, the highest Linpack score — a measurement of a system’s floating point computing horsepower — in a global supercomputing competition held in conjunction with SC18 in Dallas. Continue reading “NTU achieves highest Linpack score in global supercomputing competition”
China artificial intelligence (AI) company SenseTime has inked memoranda of understanding (MOU) with Nanyang Technological University (NTU), National Supercomputing Centre of Singapore (NSCC) and Singtel.
First, it was Singapore Management University (SMU). Now two other Singapore universities — Singapore University of Technology and Design (SUTD) and Nanyang Technological University (NTU) — have also deployed the NVIDIA DGX-1 deep learning supercomputer for their research projects on artificial intelligence (AI).
SUTD will use the DGX-1 at the SUTD Brain Lab to further research into machine reasoning and distributed learning. Under a memorandum of understanding signed earlier this month, NVIDIA and SUTD will also set up the NVIDIA-SUTD AI Lab to leverage the power of GPU-accelerated neural networks for researching new theories and algorithms for AI. The agreement also provides for internship opportunities to selected students of the lab.
“Computational power is a game changer for AI research, especially in the areas of big data analytics, robotics, machine reasoning and distributed intelligence. The DGX-1 will enable us to perform significantly more experiments in the same period of time, quickening the discovery of new theories and the design of new applications,” said Professors Shaowei Lin and Georgios Piliouras, Engineering Systems and Design, SUTD.
The CUDA Teaching Center Program is designed to support and encourage teaching establishments to include GPU Computing using CUDA C/C++ as part of their course offerings.
Under the program, NVIDIA will donate CUDA enabled GPUs to be installed in teaching lab computers at NTU’s School of Computer Engineering. Students and other members of the university community will have direct access to CUDA enabled systems for hands-on experience of CUDA C/C++ development, debugging and experimentation.