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
News
Coming Summer 2016: PennAuth for Wharton HPC Services
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
Run Unlimited Jobs with the Short Queue
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
Seamless R and C++ integration with Rcpp
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
Improved Support for Parallel IPython on Wharton HPCC
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
HPCC Multi-processor Parallel Environments
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
Minimal Linux with Packer and Vagrant
As an IT professional, it’s important to take the time to sharpen your tools. And as a systems programmer and project leader in research computing, one of my most valuable tools is a lean, mean operating system install. Prior to the deployment of Wharton’s High Performance Computing Cluster (HPCC), the…Read More
Running LDA modeling on Wharton’s HPCC
I have been assisting a faculty member within the Marketing Department with an ongoing research project involving U.S. senatorial elections over the past 36 years. For each election a set of media articles were gathered along with some meta data (title, publication, etc.) making up a corpus. Each corpus contains, on average,…Read More
Parallel IPython with Univa Grid Engine (SGE)
I frequently sing the praises of Python as the go-to language for research programming. Python is extremely fast, in terms of human development time. There are typically more CPU cores available versus research assistants with specific programming skills. On that note, Python is also extremely fast, in terms of compute…Read More
How to capture MTurk workers’ IDs into your Qualtrics survey
When posting a Qualtrics survey link on MTurk, here’s how to capture a worker ID as embedded data: First, create a HIT (Human Intelligence Task) normally, selecting the Survey Link template type. Continue setting up your hit normally until you arrive at the Design Layout tab, then click the Source button and replace…Read More