Nvidia Unveils Pascal Based Tesla P100 GPU, World’s Largest FinFET Chip with 21 TFLOPs
Nvidia has revealed the Pascal based Tesla P100 GPU which is their fastest GPU to date. Touted as the largest FinFET chip on the market, Nvidia Tesla P100 GPU features 15.3 billion transistors on a 610mm2 16nm die, 16GB of HBM2 memory, and the NVLink interconnect.
Performance-wise, the Tesla P100 includes 5.3 TFLOPS using 64-bit floating-point numbers, 10.6 TFLOPS using 32-bit, and 21.2 TFLOPS using 16-bit. Further, it has 4MB of L2 cache, and a block of 14MB of shared memory. For clock speeds, Pascal GP100 runs at 1328 MHz core and 1480 MHz boost clock – which is no doubt an incredible leap for that small a chip.
Nvidia claims the GPU delivers 65 percent higher speed, around 2 times the transistor density increase and 70 percent less power than its 28HPM tech.
Key technologies incorporated in the Pascal GP100 GPU used in Tesla P100 include:
- Extreme performance—powering HPC, deep learning, and many more GPU Computing areas;
- NVLink—NVIDIA’s new high speed, high bandwidth interconnect for maximum application scalability;
- HBM2—Fastest, high capacity, extremely efficient stacked GPU memory architecture;
- Unified Memory and Compute Preemption—significantly improved programming model;
- 16nm FinFET—enables more features, higher performance, and improved power efficiency.
Based on the above five breakthrough technologies, the Tesla P100 enables “a new class of servers that can deliver the performance of hundreds of CPU server nodes,” said CEO Jen-Hsun Huang during his speech at GTC 2016.
Nvidia Tesla P100 GPU is aimed at hyperscale data center workloads crunching deep-learning AI and HPC apps. Servers with the chips are set to hit the shelves in Q1 2017, while Nvidia’s DGX-1 supercomputer, which also uses it, is due out in June.
Gohar is the lead editor at TechFrag. He has a wide range of interests when it comes to tech but he's currently spending a big chunk of his time writing about privacy, cyber security, and anything policy related.