An Open Source Platform for Virtual Supercomputing

An Open Source Platform for Virtual Supercomputing, Michael Feldman reports:

Erlang Solutions and Massive Solutions will soon launch a new cloud platform for high performance computing. Last month they announced their intent to bring a virtual supercomputer (VSC) product to market, the idea being to enable customers to share their HPC resources either externally or internally, in a cloud-like manner, all under the banner of open source software.

The platform will be based on Clustrx and Xpandrx, two HPC software operating systems that were the result of several years of work done by Erlang Solutions, based in the UK, and Massive Solutions, based in Gibraltar. Massive Solutions has been the driving force behind the development of these two OS’s, using Erlang language technology developed by its partner.

In a nutshell, Clustrx is an HPC operating system, or more accurately, middleware, which sits atop Linux, providing the management and monitoring functions for supercomputer clusters. It is run on its own small server farm of one or more nodes, which are connected to the compute servers that make up the HPC cluster. The separation between management and compute enables it to support all the major Linux distros as well as Windows HPC Server. There is a distinct Clustrx-based version of Linux for the compute side as well, called Compute Based Linux.

A couple of things to note from within the article:

The only limitation to this model is its dependency on the underlying capabilities of Linux. For example, although Xpandrx is GPU-aware, since GPU virtualization is not yet supported in any Linux distros, the VSC platform can’t support virtualization of those resources. More exotic HPC hardware technology would, likewise, be out of the virtual loop.

The common denominator for VSC is Erlang, not just the company, but the language http://www.erlang.org/, which is designed for programming massively scalable systems. The Erlang runtime has built-in to support for things like concurrency, distribution and fault tolerance. As such, it is particularly suitable for HPC system software and large-scale interprocess communication, which is why both Clustrx and Xpandrx are implemented in the language.

As computing power and access to computing power increases, have you seen an increase in robust (in your view) topic map applications?

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