This whitepaper is an excellent summary of how a next generation platform can be developed to bring a wide range of data to life, giving users the ability to take action when needed. Organizations that need to deal with massive amounts of data but are having challenges figuring out how to make sense of all of the data should read this whitepaper.
“Intel provided a wealth of machine learning announcements following the Intel Xeon Phi processor (formerly known as Knights Landing) announcement at ISC’16. Building upon the various technologies in Intel Scalable System Framework, the machine learning community can expect up to 38% better scaling over GPU-accelerated machine learning and an up to 50x speedup when using 128 Intel Xeon Phi nodes compared to a single Intel Xeon Phi node. The company also announced an up to 30x improvement in inference performance (also known as scoring or prediction) on the Intel Xeon E5 product family due to an optimized Intel Caffe plus Intel Math Kernel Library (Intel® MKL) package.”
In this video from ISC 2016, Gabriel Broner from SGI describes the company’s innovative solutions for high performance computing. “As the trusted leader in high performance computing, SGI helps companies find answers to the world’s biggest challenges. Our commitment to innovation is unwavering and focused on delivering market leading solutions in Technical Computing, Big Data Analytics, and Petascale Storage. Our solutions provide unmatched performance, scalability and efficiency for a broad range of customers.”
In this video from ISC 2016, Barry Davis from Intel describes the company’s brand new Intel Xeon Phi Processor and how it fits into the Intel Scalable System Framework. “Eliminate node bottlenecks, simplify your code modernization and build on a power-efficient architecture with the Intel Xeon Phi™ processor, a foundational element of Intel Scalable System Framework. The bootable host processor offers an integrated architecture for powerful, highly parallel performance that will pave your path to deeper insight, innovation and impact for today’s most-demanding High Performance Computing applications, including Machine Learning. Supported by a comprehensive technology roadmap and robust ecosystem, the Intel Xeon Phi processor is a future-ready solution that maximizes your return on investment by using open standards code that are flexible, portable and reusable.”
In this video from ISC 2016, Dr. Eng Lim Goh from SGI discusses the latest trends in high performance data analytics and machine learning. “Dr. Eng Lim Goh joined SGI in 1989, becoming a chief engineer in 1998 and then chief technology officer in 2000. He oversees technical computing programs with the goal to develop the next generation computer architecture for the new many-core era. His current research interest is in the progression from data intensive computing to analytics, machine learning, artificial specific to general intelligence and autonomous systems. Since joining SGI, he has continued his studies in human perception for user interfaces and virtual and augmented reality.”
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.”
“Supercomputers are key to the Cancer Moonshot. These exceptionally high-powered machines have the potential to greatly accelerate the development of cancer therapies by finding patterns in massive datasets too large for human analysis. Supercomputers can help us better understand the complexity of cancer development, identify novel and effective treatments, and help elucidate patterns in vast and complex data sets that advance our understanding of cancer.”
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.”
OCF in the UK reports that the company continues to expand its operations. The high performance computing integrator is recruiting a number of new staff to meet the growing appetite and demand for HPC and data analytics solutions across universities, research institutes and commercial businesses in the UK.