In this video from the Intel HPC Developer Conference, Justin Gottschlich, PhD from Intel describes how the company doubling down on Anomaly Detection using Machine Learning and Intel technologies. “In this talk, we present future research directions at Intel Labs using deep learning for anomaly detection and management. We discuss the required machine learning characteristics for such systems, ranging from zero positive learning, automatic feature extraction, and real-time reinforcement learning. We also discuss the general applicability of such anomaly detection systems across multiple domains such as data centers, autonomous vehicles, and high performance computing.”
Demonstrating Asetek’s adaptability to any data center cooling need, HPC installations from around the world are currently on display at SC16 in Salt Lake City, Utah November 14-17. Servers from these installations featuring Asetek liquid cooling will be on display including servers installed at Oakforest-PACS, the highest Performance Supercomputer System in Japan.
Watch this video of Nvidia CEO Jen-Hsun Huang’s talk from SC16 in Salt Lake City. Can’t make it to the show? Tune in right here on insideHPC to watch Nvidia talks all this week. “See how other leaders in the field are advancing computational science across domains, get free hands-on training with the newest GPU-accelerated solutions, and connect with NVIDIA experts.”
Today Aquila announced a liquid-cooled edge data center co-development program featuring the first ruggedized modular edge data center developed around the Aquarius liquid cooled compute platform. This platform combines TAS’s industry-leading efficient modular data centers with Aquarius’s liquid cooled compute, switching, and storage to address the need for small modular data centers.
The new TOP500 list is out, and Rad is Free HPC is here podcasting the scoop in their own special way. With two new systems in the TOP10, there are many different perspectives to share. “The Cori supercomputer, a Cray XC40 system installed at Berkeley Lab’s National Energy Research Scientific Computing Center (NERSC), slipped into the number 5 slot with a Linpack rating of 14.0 petaflops. Right behind it at number 6 is the new Oakforest-PACS supercomputer, a Fujitsu PRIMERGY CX1640 M1 cluster, which recorded a Linpack mark of 13.6 petaflops.”
FPGAs will become increasing important for organizations that have a wide range of applications that can benefit from performance increases. Rather than a brute force method to increasing performance in a data center by purchasing and maintaining racks of hardware and associated costs, FPGAs may be able to equal and exceed the performance of additional servers, while reducing costs as well.
Today Seagate Technology introduced the ClusterStor 300N storage system with Nytro Intelligent I/O Manager, the newest addition to its family of scale-out storage systems for high-performance computing and the first with a flash cache accelerator. “Seagate’s ClusterStor 300N expands on our proven, engineered systems approach that delivers performance efficiency and value for HPC environments of any size, using a hybrid technology architecture to handle tough workloads at a fraction of the cost of all-flash approaches.”
Welcome to the Mobile Edition for the Print ‘n Fly Guide to SC16 in Salt Lake City. Inside this guide you will find technical features on supercomputing, HPC interconnects, and the latest developments on the road to exascale. It also has great recommendations on food, entertainment, and transportation in SLC.
Today Penguin Computing announced several important achievements of its Penguin Computing On-Demand (POD) HPC cloud service, including a recent 50 percent increase in capacity and plans to double POD’s total capacity in Q1 2017. The upgrade will include new Intel Xeon processors and Intel Omni-Path architecture. “Rapid demand for and growth in our POD business reflects the significant benefits customers are experiencing, particularly since we announced availability of the OCP-compliant Tundra platform on POD late last year,” said Tom Coull, President and CEO, Penguin Computing. “With the Tundra platform, our customers have greater capacity due to faster scaling combined with increased performance and streamlined costs. Tundra on POD also highlights the growth and maturing market role of open computing, with thousands of high-speed, cost-efficient cores available to meet customers’ needs for faster, easier deployment of capacity at a low cost.”
In this video from the Intel HPC Developer Conference, Ananth Sankaranarayanan from Intel describes how the company is optimizing Machine Learning frameworks for Intel platforms. Open source frameworks often are not optimized for a particular chip, but bringing Intel’s developer tools to bear can result in significant speedups. For meaningful impact and business value, organizations require that the time to train a deep learning model be reduced from weeks to hours. In this talk, we will present the details of the optimization and characterization of Intel-Caffe and the support of new deep learning convolutional neural network primitives in the Intel Math Kernel Library.”