In this Chip Chat podcast, Bill Mannel, Vice President and General Manager for HPC and Big Data from Hewlett Packard Enterprise (HPE) describes the High Performance Computing Alliance between HPE and Intel. He highlights how the two companies are developing innovative solutions based on Intel Scalable System Framework (Intel SSF) and are working to enhance HPC solutions while engaging customers directly in centers of excellence (COEs) located in Grenoble, France and Houston, Texas. Bill also emphasizes how HPE compute solutions are experiencing incredible momentum in government, commercial and academic market verticals and that HPE is receiving excellent results from the integration of HPE Apollo products and Intel HPC technology.
Today Intel Corporation announced that it has completed the acquisition of Altera, a leading provider of field-programmable gate array (FPGA) technology. The acquisition complements Intel’s leading-edge product portfolio and enables new classes of products in the high-growth data center and Internet of Things (IoT) market segments.
In this video from SC15, Dr. Eng Lim Goh from SGI describes how the company is embracing new HPC technology trends such as new memory hierarchies. With the convergence of HPC and Big Data as a growing trend, SGI is envisions a “Zero Copy Architecture” that would bring together a traditional supercomputer with a Big Data analytics machine in a way that would not require users to move their data between systems.
“Analytics applied over complex, many-to-many data relationships hit the ‘Graph Cache Thrash’ bottleneck and grind to a halt, failing to deliver good performance or to operate at scale,” said Brad Bebee, SYSTAP CEO. “GPU hardware provides a compelling performance increase for data-intensive, predictive analytic applications. With Blazegraph and our new GPU products, users can harness the computing power comparable to what was only available from supercomputers, such as a Cray, at a fraction of the cost.”
“Applications in diverse industries such as the hospitality and retail industry, social networks and surveillance can benefit from real time image recognition. Parallelism at the system level can be divided into two main areas. First, at the database level and second at the image recognition level. The compute load per thread on the host system can just be calculated as the total number of images in the database divided by the number of threads. The image matching algorithms can then be parallelized on the coprocessor.”
Baidu Research has unveiled new research results from its Silicon Valley AI Lab (SVAIL). Results include the ability to accurately recognize both English and Mandarin with a single learning algorithm. The results are detailed in a paper: Deep Speech 2: End-to-End Speech Recognition in English and Mandarin.
Today IBM’s Cleversafe announced its software defined/hardware aware storage approach to enable organizations with massive-scale data demands to easily take advantage of software defined storage (SDS) with a solution that integrates with industry-standard hardware. The Cleversafe approach reduces cost and complexity by enabling enterprises to manage their storage hardware and software from a single management system. The company also announced newly certified hardware platforms, giving enterprise customers even greater deployment flexibility.
“This talk will discuss the plans to use OpenStack to manage and automate dynamically changing an environment to provide users a highly re-configurable software environment with access to a large number of operating systems and software packages on the “Bridges system.” It will feature elements of OpenStack related to bare-metal booting, network provisioning, container management, storage, and scheduling nodes to match the workloads of the users.”
In this video from SC15, Bryan Catanzaro, senior researcher in Baidu Research’s Silicon Valley AI Lab describes AI projects at Baidu and how the team uses HPC to scale deep learning. Advancements in High Performance Computing are enabling researchers worldwide to make great progress in AI.
Today Nvidia announced that Facebook will power its next-generation computing system with Tesla GPUs, enabling a broad range of new machine learning applications.