Cluster Design

By definition, all clusters are unique computing machines. The possible combinations of hardware, software and user requirements makes designing an optimum cluster difficult, but certainly not impossible given some background and rules of thumb.

The Best of Both Worlds: Low Cost and Large Scale OpenMP and MPI

Take a moment and ask yourself the following question:

If you can have both large scale OpenMP and MPI performance in an easy to manage single system image built from commodity hardware and price points, would you prefer that a solution?

This very question was the subject a recent white paper: Redefining Scalable OpenMP and MPI Price-to-Performance with Numascale’s NumaConnect published by Numascale.

Numascale has been perfecting the NumaConnect technology and has now published several benchmarks that show both excellent shared (OpenMP) and distributed (MPI) memory performance. A Numascale cluster uses commodity hardware and the “pug-and-play” NumaConnect interconnect to deliver the ease of shared memory programming and administration at standard HPC cluster price points. One running system currently offers users over 1,700 cores with a 4.6 TByte single memory image.

Read more: The Best of Both Worlds: Low Cost and Large Scale OpenMP and MPI

Key Questions to Ask When Going Parallel

Software continues to be one of the largest challenges to the parallel computing market. When considering parallel and multi-core computing, questions about software are most important. To help set expectations and ensure a successful project, Interactive Supercomputing has prepared some important questions worth asking about parallel software (and some answers!).

Introduction

A growing number of problems demand parallel computing capabilities these days, and the processing power of high performance technical computing servers have kept pace with this demand. Yet a hurdle to unlocking the true potential of parallel computing remains: affordable, easy-to-use parallel programming tools. The "software gap" – the gap between hardware capabilities and actual benefits we can extract through programming – is growing wider. Many applications are available for parallel computers, yet the custom development required by these tools is exceedingly complex, takes months or years to develop, and runs in batch mode over hours or days.

Read more: Key Questions to Ask When Going Parallel

A Web-Based Tool for Optimized Cluster Design

Read this article and become a cluster design expert! Use a new tool from the aggregate.org to determine price and performance before you buy! Get a handle on everything from Ethernet cables, to GFLOPS, to power and cooling. ClusterMonkey likes to call it the Clustanator, you will probably call it extremely useful.

Whenever someone asks what hardware to buy for their new cluster, the answer is always, "It depends." It depends on what application the cluster will be used for, it depends on how much space, power, and cooling are available, it depends on the costs of operating the cluster, and it depends on how much the parts that might be used cost. The standard process is to analyze the application and use rules of thumb and experience to guess what hardware will work best. The sophistication of the analysis depends on how much money is involved and how much computer engineering expertise the designer has.

Read more: A Web-Based Tool for Optimized Cluster Design

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