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DDN: Practical Approaches to Emerging, Large-Scale Data Problems

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In this video from the HPCAC Swiss Conference 2014, James Coomer from DDN presents: Practical Approaches to Emerging, Large-Scale Data Problems.

Ingram Micro Artizen Soutions for HPC

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In this video from the GPU Technology Conference, Rick Young from Ingram Micro describes the company’s Artizen HPC solutions. “Available now to channel partners in the U.S., the distributor’s new and exclusive line of Artizen High Performance Computing (HPC) offerings include turnkey high performance servers, ultimate workstations, and customizable supercomputing clusters, as well as computing integration and software installation services.”

Monitoring and Management Interfaces for GPU Devices in a Cluster Environment

sadaf

“This presentation will provide an overview of the Nvidia Tesla Deployment Kit (TDK) from a user and a system administrator point of view. TDL contains Nvidia Management Library (NVML) and nvidia-healthmon–a tool for detecting and troubleshooting known GPU issues in a cluster environment. Usage models within a cluster environment will be presented along with a discussion on how existing resource management tools can be extended to improve allocation and accounting of GPU resources.”

Video: The OpenPower Initiative

gilad

“The OpenPOWER Foundation intends to build advanced server, networking, storage and acceleration technology aimed at delivering more choice, control and flexibility to developers of next-generation, hyperscale and cloud data centers.”

HPC Trends for 2014

Based on the latest survey data, Michael Feldman of Intersect360 Research will discuss the top trends of that emerged in 2013, with a look ahead to how the market will continue to evolve in the year ahead. Topics will include HPC in the Cloud, Big Data, evolutions in processor architectures, and the race to Exascale.

Video: ClusterStor Update

torben

“HPC storage solutions and futures continue to evolve as growth and performance requirements permeate every HPC market segment. Torben discusses these challenges and how the company’s storage solutions are addressing these shifting needs with new developments around disk drives, RAID, CIFS, security, small file handling, and other related technologies.”

Managing the GPUs of Your Cluster in a Flexible Way with rCUDA

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In this talk, we introduce the rCUDA remote GPU virtualization framework, which has been shown to be the only one that supports the most recent CUDA versions, in addition to leverage the InfiniBand interconnect for the sake of performance. Furthermore, we also present the last developments within this framework, related with the use of low-power processors, enhanced job schedulers, and virtual machine environments.”

DK Panda Presents: Programming Models for Exascale Systems

panda

“This talk will focus on programming models and their designs for upcoming exascale systems with millions of processors and accelerators. Current status and future trends of MPI and PGAS (UPC and OpenSHMEM) programming models will be presented. We will discuss challenges in designing runtime environments for these programming models by taking into account support for multi-core, high-performance networks, GPGPUs, Intel MIC, scalable collectives (multi-core-aware, topology-aware, and power-aware), non-blocking collectives using Offload framework, one-sided RMA operations, schemes and architectures for fault-tolerance/fault-resilience.”

Negative Latency and Einstein Express

“I’ve been thinking for a while that our obsession with reduction of latency in computing and storage could be ameliorated by exploiting a negative latency design. A negative latency design would be one where a hypothetical message would arrive at a receiver before the sender completed sending it.”

Monitoring and Management Interfaces for GPU Devices in a Cluster Environment

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“This presentation will provide an overview of the Nvidia Tesla Deployment Kit (TDK) from a user and a system administrator point of view. TDL contains Nvidia Management Library (NVML) and nvidia-healthmon–a tool for detecting and troubleshooting known GPU issues in a cluster environment. Usage models within a cluster environment will be presented along with a discussion on how existing resource management tools can be extended to improve allocation and accounting of GPU resources.”