![]() When can we expect Volta-based GPUs for desktops? It’s difficult to say, especially with the supply of the HBM2 DRAM somewhat limited and the variety of timetables NVIDIA has followed in the past. The Tesla V100 GPU will likely make its debut in the new $149,000 DGX-1 supercomputer which is scheduled to ship in the 3rd quarter of this year. CEO Jason Huang shows a comparison in deep learning performance in hours on the Kepler, Pascal, and Volta architectures. For AI, the new Tensor cores provide a 5x performance improvement compared to using CUDA on the previous generation Pascal GPUs. The new Tensor cores are designed specifically for deep learning, providing a 4×4 matrix array that processes calculations in parallel. The 5120 CUDA cores in the V100 compares with 3840 cores in the TITAN Xp or Quadro P6000. ![]() NVLink (card to card inter-connection) now provides 300GB/sec of bandwidth, an increase from Pascal’s 160GB/secĪs a general benchmark, this GPU architecture provides a 1.5x performance improvement for CUDA operations.Tensor cores provide 120 teraflops of deep learning performance, effectively equivalent to the performance of 100 CPUs.640 Tensor cores (new cores designed for AI workflows).15 teraflops of processing power for 32-bit floating point operations (CUDA).7.5 teraflops of processing power for 64-bit floating point operations (CUDA).Overall size 815mm² - about the size of an Apple Watch.21 billion transistors in a 12 nanometer manufacturing process.This is the successor to the “Pascal” architecture, which was announced at last year’s GTC. Huang announced the first GPU in NVIDIA’s new Volta architecture, the Tesla V100 Data Center GPU. First Volta GPU coming soon The new NVIDIA Tesla V100 GPU The crew at NVIDIA also alluded to vfx and post related announcements coming out closer to SIGGRAPH, which has a greater focus on the industry. So while the buzzword today in San Jose was “AI”, there were still many interesting takeaways from the keynote and announcements today including Iray AI, Mental Ray for 3DSMax improvements, and more. That being said, the growth of the use of GPUs for machine learning, artificial intelligence, and neural networks has increased dramatically in comparison to post. We’ve documented the increase of the use of GPU processing in the visual effects industry, especially as the processing power in GPUs has outpaced that of CPUs. This reflects an increase in the overall number of CUDA developers, which Huang pegged at over 50,000 - a 10x increase over five years ago. NVIDIA’s conference has grown dramatically over the years, with the number of attendees to the San Jose conference tripling over the last three years. The growth in this area of the industry is clear. ![]() The 2017 GPU Technology Conference keynote address by NVIDIA CEO Jensen Huang took place today and focused on the new Tesla Volta V100 as well as the promise of machine learning and artificial intelligence.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |