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New HP Apollo 4000 Systems Fulfill Booming Big Data Analytics & Object Storage Requirements

Apollo4530_Gen9_Server_TOP

High Performance Computing and Big Data analytics touch us every day. We each rely on daily weather forecasts, banking and financial information, scientific and health analyses, and thousands of other activities that involve HPC and Big Data analysis.

HPC in Medical Applications

onestop1

Medical applications like CT (computed tomography) scanning and MRI (magnetic resonance imaging) require quick, accurate results from processing complex algorithms. So reducing the compute time required is a primary challenge to manufacturers of CT and MRI equipment.

Computing With MPI in Heterogeneous Environments

Stampede

Designating the appropriate provider for large MPI applications is critical to taking advantage of all of the compute power available. “A modern HPC system with multiple host cpus and multiple coprocessors such as the Intel Xeon Phi coprocessor housed in numerous racks can be optimized for maximum application performance with intelligent thread placement.”

Concurrent Kernel Offloading

phi

“The combination of using a host cpu such as an Intel Xeon combined with a dedicated coprocessor such as the Intel Xeon Phi coprocessor has been shown in many cases to improve the performance of an application by significant amounts. When the datasets are large enough, it makes sense to offload as much of the workload as possible. But is this the case when the potential offload data sets are not as large?”

Hero Performance is about the Applications

David Lecomber, CEO, Allinea

During last month’s PRACE Days in Dublin – where I enjoyed talks on improvements in codes and methods in areas as diverse as CFD, RTM in geophysics, and in genomics – I saw once again that “hero” performance improvements happen and happen regularly.

Load Balancing Using OpenMP 4.0

OpenMP

OpenMP 4.0 standard now allows for the offloading of portions of the application, in order to take more advantage of many-core accelerators such as the Intel Xeon Phi coprocessor.

Solving Eight Constraints of Today’s Data Center

data center cooling

With the growth of big data, cloud and high performance computing, demands on data centers around the world are expanding every year. Unfortunately, these demands are coming up against significant opposition in the form of operating constraints, capital constraints, and sustainability goals. In this article, we look at 8 of these constraints and how direct-to-chip liquid cooling is solving them.

Clusters Drive Design Simulation

IBM Cluster

As design challenges become more complex and time to product launches are reduced, it is important to understand how to use a cluster for simulation, as compared to just a single node. “HPC Clusters Drive Design Optimization” is an excellent introduction on how to get the most out of a compute cluster.

N-Body Methods Optimization

phi

“N-Body problems compare the interaction of N-bodies against N-bodies, which results in calculations of the order of N2. As this can be computationally very expensive, but a well understood process, techniques and optimizations can be performed on application code using compiler directives and easy to understand techniques.”

Direct N-Body Simulation

galaxy_s

In some domains, an N-Body simulation is key to solving for the movement and forces of a dynamic system of particles. At each time step, the force that one body exacts on each other, and then the velocity can be computed. The simulation can continue up to a desired number of time steps.