HPC systems are really designed to be shared by several users. One way to share them is through a software tool called a resource manager. Openlava is an open source version of the commercial scheduler LSF. It shares the robustness of LSF while being freely available, very scalable, and easy to install and customize.

Gathering data on various aspects of your HPC system is a key step toward developing information about the system and one of the first steps toward tuning your system for performance and reporting on system use. It can tell how users are using the system and, at a high level, what they are doing. In this article, I present a method for gathering data on how users are using Environment Modules, such as which modules are being used, how often, and so on.

The Julia language is a very powerful parallel computing model that works across multiple cores and cluster nodes.

Installing and configuring Warewulf on the master node and booting the compute nodes creates a basic cluster installation; however, a little more configuration to the master remains and a few other tools must be installed and configured for the Warewulf cluster to become truly useful for running HPC applications.

Can this new language deliver on bold claims of fast, easy, and parallel?

The Warewulf stateless cluster tool is scalable and highly configurable, and it eases the installation, management, and monitoring of HPC clusters.

Sure, you could pay for cloud services, but with GlusterFS, you can take the idle space in your own data center and create a large data warehouse quickly and easily.

Stepping Back to Move Forward: Breaking the rules could offer some new avenues for the future of HPC.

The US Department of Energy (DOE) in December issued a detailed report summarizing the Magellan project, which investigated the role of cloud computing, addressing the HPC computing needs of scientists funded by the DOE Office of Science.

HPC Storage is arguably one of the most pressing issues in HPC. Selecting various HPC Storage solutions is a problem that requires some research, study, and planning to be effective – particularly cost-effective. Getting this process started usually means understanding how your applications perform I/O. This article presents some techniques for examining I/O patterns in HPC applications.