Welcome to Julia Julia is now installed across all compute servers of Wharton’s HPC systems. From the Julia Website: Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution,…Read More

We have added 1.5 terabytes of memory to The Wharton High-Performance Computing Cluster (HPCC). This upgrade takes the system to over 6TB of total available memory for our research computing needs. After the upgrade, we now have three compute nodes with half a terabyte of memory each! This is a…Read More

DEPRECATED! We’re working on documentation for connecting to WRDS via their newer PostgreSQL service See https://wrds-www.wharton.upenn.edu/pages/support/programming-wrds/ for details for newest methods … some adjustments to the WRDS documentation are needed, generally installing any libraries, packages, or modules required (Python: ‘wrds’, R: RPostgres, etc.) Original Article (DEPRECATED): Using Wharton Research Computing’s…Read More

What’s Happening, and Why? In compliance with Wharton and Penn’s plans to more thoroughly integrate user accounts, we will be moving to Penn authentication (PennAuth) in the Summer of 2016. PennAuth provides higher levels of accountability and compliance with current research security standards, as well as a more seamless experience across Penn…Read More

The short.q job queue on the Wharton High Performance Computing Cluster (HPCC) is now available for general use. What this means is that all users may now have up to 256 more jobs simultaneously running! This is a way around the current 64-core limit. To use this new feature, one may…Read More

Are you an R programmer? Do you like high-performance computing? Do you want to accelerate your core R functions? Do you sound like a pirate when you talk about your code? Then, this book may be for you: Seamless R and C++ integration with Rcpp Rcpp is an R add-on…Read More

You may have seen my previous post on Parallel IPython with Univa Grid Engine (SGE). It involved a fair bit of step-by-step configuration and large chunks of boilerplate code. Well, that has now been simplified. It is now much easier to run Python functions across a hundred CPU cores on…Read More

The Wharton High-Performance Computing Cluster (HPCC) system is a powerful environment for running research code – code that may require a long run-time, a lot of memory, or numerous iterations. By default, research code on HPCC will run as a job with access to a single CPU core. However, by…Read More