Collaborations

Evaluating the Benefits of An Extended Memory Hierarchy for Parallel Streamline Algorithms

The visualization groups at LBL and SDSC teamed up to study the performance of commonly used visualization algorithms for streamlining computing on Dash. By modifying the algorithm to use disk-based cache, the group saw an increase of two to five fold over traditional methods. Specifically, the group found that the fast storage times of SSDs led to significant gains over local hard drives in some cases. The study will be presented at the "IEEE Symposium on Large-Scale Data Analysis and Visualization" at Providence, RI, USA on October 23–24, 2011.

Large Synoptic Survey Telescope
Moving Object Pipleline System  (MOPS)

The goal of the MOPS project is to identify asteroids and other transient near-earth objects from images that will be collected by the Large Synoptic Survey Telescope (LSST). Working with synthetic data, we are collaborating with the LSST software team to develop fast, efficient algorithms for several stages of the data processing pipeline. Through a combination of serial optimizations and implementation of thread-level parallelism, the time to solution for two key steps of the process – removal of subset tracks and linking togther of “tracklets”  to form complete tracks – has already been reduced by 4–20x. Due to the need for large, shared memory, the software is ideally suited for the vSMP nodes on Dash and Gordon.

Michael Gilson Laboratory, UCSD School of Pharmacy
Sampling Conformations of Small Molecules

In recent years, the Gilson Lab has developed a novel technique for generating molecular conformations and their associated normalized probabilities. This approach makes it possible to straightforwardly calculate thermodynamic quantities that are not accessible using molecular dynamics. A drawback of the technique is that for many systems of interest, the shared memory requirements far exceed that available on standard HPC hardware. For example, a molecule consisting of just 62 atoms will need approximately 100 GB of memory. Collaborative efforts between SDSC and the Gilson Lab have resulted in dramatic performance improvments to the software that will make it possible to solve problems that have previously been considered intractable. Work is underway to parallelize the sampling algorithms and optimize the patterns of memory access for the Dash/Gordon vSMP nodes.

Recent Gordon News & Events

Data Oasis Expansion Progress

April 30, 2013
Update on Data Oasis expansion As of April 5, 2013, we have completed the expansion of the SDSC Data Oasis projects space and the new filesystem is n...   more news...


Grand Challenges in Data-Intensive Discovery

10/26/10   -   10/28/10
"Grand Challenges in Data-Intensive Discovery" conference was held October 26 - 28, 2010 at the San Diego Supercomputer Center (SDSC) on the campus o...   more events...


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