NVIDIA Expands Its Deep Learning Inference Capabilities for Hyperscale Datacenters
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NVIDIA’s (NASDAQ:NVDA) invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. More information at http://nvidianews.nvidia.com/.
- Total cost of ownership based on a workload mix representative of a major cloud service provider: 60 percent neural collaborative filtering (NCF), 20 percent neural machine translation (NMT), 15 percent automatic speech recognition (ASR), 5 percent computer vision (CV) and per socket (Tesla V100 GPU vs CPU) workload speedups of: 10x NCF, 20x NMT, 15x ASR, 40x CV. CPU node configuration is two-socket Intel Skylake 6130. GPU recommended node configuration is the eight Volta HGX-1.
- Performance gains observed over a range of important workloads. Examples include ResNet50 v1 inference performance at a 7 ms latency is 190x faster with TensorRT on a Tesla V100 GPU than using TensorFlow on a single-socket Intel Skylake 6140 at minimum latency (batch = 1).
Certain statements in this press release including, but not limited to, statements as to: the benefits, impact, performance, uses and abilities of NVIDIA TensorRT 4 and its integration into the TensorFlow framework; GPU acceleration for deep learning inference gaining traction and its impact and benefits; the benefits and impact of NVIDIA working with Kaldi to optimize GPUs, NVIDIA collaborating with partners, TensorRT being used around the world, GPU acceleration for Kubernetes, NVIDIA Tesla GPU-accelerated servers and MATLAB software’s integration of TensorRT; NVIDIA’s technologies expanding its potential inference market; and the support for intelligent applications and frameworks improving the quality of deep learning and reducing costs of hyperscale servers are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the reports NVIDIA files with the Securities and Exchange Commission, or SEC, including its Form 10- K for the fiscal period ended January 28, 2018. Copies of reports filed with the SEC are posted on the company’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.
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