NVIDIA Corporation (NASDAQ:NVDA) introduced the NVIDIA® Tesla® P100 GPU accelerator for PCIe servers, which delivers massive leaps in performance and value compared with CPU-based systems.
Demand for supercomputing cycles is higher than ever. The majority of scientists are unable to secure adequate time on supercomputing systems to conduct their research, based on National Science Foundation data.1 In addition, high performance computing (HPC) technologies are increasingly required to power computationally intensive deep learning applications, while researchers are applying AI techniques to drive advances in traditional scientific fields.
The Tesla P100 GPU accelerator for PCIe meets these computational demands through the unmatched performance and efficiency of the NVIDIA Pascal™ GPU architecture. It enables the creation of “super nodes” that provide the throughput of more than 32 commodity CPU-based nodes and deliver up to 70 percent lower capital and operational costs.
“Accelerated computing is the only path forward to keep up with researchers’ insatiable demand for HPC and AI supercomputing,” said Ian Buck, vice president of accelerated computing at NVIDIA. “Deploying CPU-only systems to meet this demand would require large numbers of commodity compute nodes, leading to substantially increased costs without proportional performance gains. Dramatically scaling performance with fewer, more powerful Tesla P100-powered nodes puts more dollars into computing instead of vast infrastructure overhead.”
The Tesla P100 for PCIe is available in a standard PCIe form factor and is compatible with today’s GPU-accelerated servers. It is optimized to power the most computationally intensive AI and HPC data center applications. A single Tesla P100-powered server delivers higher performance than 50 CPU-only server nodes when running the AMBER molecular dynamics code,3 and is faster than 32 CPU-only nodes when running the VASP material science application.
Later this year, Tesla P100 accelerators for PCIe will power an upgraded version of Europe’s fastest supercomputer, the Piz Daint system at the Swiss National Supercomputing Center in Lugano, Switzerland.
“Tesla P100 accelerators deliver new levels of performance and efficiency to address some of the most important computational challenges of our time,” said Thomas Schulthess, professor of computational physics at ETH Zurich and director of the Swiss National Supercomputing Center. “The upgrade of 4,500 GPU-accelerated nodes on Piz Daint to Tesla P100 GPUs will more than double the system’s performance, enabling researchers to achieve breakthroughs in a range of fields, including cosmology, materials science, seismology and climatology.” (Original Source)
Shares of Nvidia are up 1.31% to $47.33 in after-hours trading. NVDA has a 1-year high of $47.77 and a 1-year low of $19.09. The stock’s 50-day moving average is $42.82 and its 200-day moving average is $34.73.
On the ratings front, Nvidia has been the subject of a number of recent research reports. In a report issued on June 17, RBC analyst Mitch Steves reiterated a Buy rating on NVDA, with a price target of $47, which represents a slight upside potential from current levels. Separately, on June 16, Canaccord Genuity’s Matt Ramsay reiterated a Buy rating on the stock and has a price target of $55.
According to TipRanks.com, which ranks over 7,500 financial analysts and bloggers to gauge the performance of their past recommendations, Mitch Steves and Matt Ramsay have a total average return of -7.0% and -1.8% respectively. Steves has a success rate of 40.0% and is ranked #3235 out of 3974 analysts, while Ramsay has a success rate of 47.0% and is ranked #3160.
The street is mostly Bullish on NVDA stock. Out of 24 analysts who cover the stock, 14 suggest a Buy rating , 9 suggest a Hold and one recommends to Sell the stock. The 12-month average price target assigned to the stock is $44.46, which represents a slight downside potential from current levels.
NVIDIA Corp. is a visual computing company, connecting people through computer graphics. It is engaged in creating graphics chips, which is used in personal computers. The company operates through two segments: Graphics Processing Unit (GPU) and Tegra Processor. The GPU segment includes sales of the company’s GeForce discrete and chipset products that supports desktop and notebook PCs plus license fees from Intel and sales of memory products. The Tegra Processors segment provides processors that deliver superior visual and multimedia experience on tablets, smart phones and gaming devices while consuming minimal power. Tegra processor is a system-on-a-chip, integrating an entire computer on a single chip. Tegra processors incorporate multi-core GPUs and CPUs together with audio, video and input/output capabilities. Tegra runs devices like smartphones, tablets and PCs; it can also be embedded into smart devices, such as televisions, monitors, set-top boxes, gaming devices and cars.