When I/O Workloads Don’t Perform

Isolating and diagnosing the root causes of your performance troubles.

Preload Trick

By using the LD_PRELOAD environment variable, you can improve performance without making changes to applications.

New Monitoring Tools

If you like ASCII-based monitoring tools, take a look at three new tools – Zenith, Bpytop, and Bottom.

Desktop Supercomputers: Past, Present, and Future

Desktop supercomputers give individual users control over compute power to run applications locally at will.

Rethinking RAID (on Linux)

Configure redundant storage arrays to boost overall data access throughput while maintaining fault tolerance.

How Linux and Beowulf Drove Desktop Supercomputing

Open source software and tools, the Beowulf Project, and communities changed the face of high-performance computing.

A Brief History of Supercomputers

This first article of a series looks at the forces that have driven desktop supercomputing, beginning with the history of PC and supercomputing processors through the 1990s into the early 2000s.

Remora – Resource Monitoring for Users

Remora provides per-node and per-job resource utilization data that can be used to understand how an application performs on the system through a combination of profiling and system monitoring.

mpi4py – High-Performance Distributed Python

Tap into the power of MPI to run distributed Python code on your laptop at scale.

Why Good Applications Don’t Scale

You have parallelized your serial application, but as you use more cores you are not seeing any improvement in performance. What gives?