In this slidecast, Marc Hamilton from describes the Nvidia Tesla P100 for PCIe Servers. “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, and is faster than 32 CPU-only nodes when running the VASP material science applications.”
“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.”
Today Italy’s E4 Computer Engineering announced plans to showcase of new NVIDIA GPU-accelerated OpenPOWER servers at ISC 2016 in Frankfurt. “For this edition of ISC16, we wanted to reinforce the message that E4 is a company that actively engages and pursues new technologies’ paths with the aim to deliver leading-edge solutions for a number of demanding environments,” said Piero Altoè, Marketing and BDM Manager, E4 Computer Engineering. “Our priority is to collaborate with organizations such as OpenPOWER Foundation and true visionaries like NVIDIA in order to obtain powerful, scalable and affordable solutions for a number of complex applications and contribute to the development of technologies that have a huge impact on many aspects of our lives.”
For Universities and Colleges that have a traditional infrastructure, adding new programs and applications is a huge endeavor. The IT staff needs to determine if all of the hardware meets the installation requirements and how to deploy these new programs on different models of desktops and notebooks. With a VDI environment that utilizes simple boot-up devices that connect to virtual desktops on the school’s server, the IT staff doesn’t have to worry about the age and capability of each individual PC when installing new software.
Today NVIDIA unveiled a comprehensive global program to support the innovation and growth of startups that are driving new breakthroughs in artificial intelligence and data science. “The NVIDIA Inception Program provides unique tools, resources and opportunities to the waves of entrepreneurs starting new companies, so they can develop products and services with a first-mover advantage.”
Today One Stop Systems announced that its the GPUltima product line now employs Bright Computing’s HPC Cluster Manager software. Bright Computing is a provider of comprehensive software solutions for provisioning and managing HPC clusters. Where conventional computer cluster systems use CPUs as the primary data processor, the GPUltima employs numbers of GPU cards, providing 10 times the performance by adding thousands more cores,” said Steve Cooper, CEO of One Stop Systems. “The GPUltima is completely ‘application-ready’, configured and tested to the customer’s specifications, so that the customer can begin processing immediately. The unique cluster management and monitoring software and the service and support packages that accompany the GPUltima make this a user-friendly system that allows the customer to begin his work without having to configure the cluster.”
Chris Mason from Acceleware presented this talk at GTC 2016. “This session will focus on real life examples including an RF powered contact lens, a wireless capsule endoscopy, and a smart watch. The session will also outline the basics of the subgridding algorithm along with the GPU implementation and the development challenges. Performance results will illustrate the significant reduction in computation times when using a localized subgridded mesh running on an NVIDIA Tesla GPU.”
The International Workshop on Communication Architectures at Extreme Scale has published its Advance Agenda. Now in its second year, Exacom 2016 will be held in conjunction with ISC 2016 in Frankfurt on Thursday, June 23, 2016.
In this video from PYCON 2016 in Portland, Lorena Barba from George Washinton University presents: Beyond Learning to Program, Education, Open Source Culture, Structured Collaboration, and Language. “PyCon is the largest annual gathering for the community using and developing the open-source Python programming language.”
In this Programming Throwdown podcast, Mark Harris from Nvidia describes Cuda programming for GPUs. “CUDA is a parallel computing platform and programming model invented by NVIDIA. It enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU). With millions of CUDA-enabled GPUs sold to date, software developers, scientists and researchers are finding broad-ranging uses for GPU computing with CUDA.”