Entries by hkrishnan@lbl.gov

Berkeley Lab Climate Software Honored for Pattern Recognition Advances

original article: http://www.nersc.gov/news-publications/nersc-news/nersc-center-news/2015/berkeley-lab-climate-software-honored-for-pattern-recognition-advances/ Contact: Kathy Kincade, +1 510 495 2124, kkincade@lbl.gov The Toolkit for Extreme Climate Analysis (TECA), developed at Lawrence Berkeley National Laboratory to help climate researchers detect extreme weather events in large datasets, has been recognized for its achievements in solving large-scale pattern recognition problems. “TECA: Petascale Pattern Recognition for Climate Science,” a paper […]

Juelich Supercomputing Center Prize Winner

UPDATE: Award Press Release! http://www.nersc.gov/news-publications/nersc-news/nersc-center-news/2015/berkeley-lab-climate-software-honored-for-pattern-recognition-advances/ “TECA: Petascale Pattern Recognition for Climate Science’ paper at CAIP has won the Juelich Supercomputing Center prize for the best application of HPC for solving a pattern recognition problem (http://caip.eu.org/caip2015/awards/). The paper documents the full scale 150K core runs on hopper and 750K core runs on Mira. From the 16th […]

Using CASCADE tools at NERSC

CASCADE support on NERSC requires a simple command: On Hopper & Edison simply type: “module load cascade” This post will highlight many of the software technologies that underpin the CASCADE environment. In future blog posts, we will delve into each technology and provide examples on how to exercise them. Technologies provided within the CASCADE module: […]

How to run UV-CDAT in parallel at NERSC

  **[Michael Wehner](mailto:mfwehner@lbl.gov) and [Hari Krishnan](mailto:hkrishnan@lbl.gov), Lawrence Berkeley National Laboratory** ## Introduction Most climate data analyses have at least one dimension that be exploited at NERSC in an embarrassingly parallel manner. In fact, the most common of these is simply time. The scripts presented here are a general solution to take advantage of temporal parallelism […]