Live Webcast 15th Annual Charm++ Workshop

Older Projects:
Cluster Computing at PPL
Cluster of workstations and PCs make an attractive platform for parallel computing. Cluster computers can be formed out of existing desktop workstations, which makes it easy for groups to embark on parallel computing projects without a capital outlay; Also, even for dedicated usage, clusters make economical parallel computers, because of the use of inexpensive commodity hardware.

We have targeted this architecture since the early days of Charm++ development. Our first versions of Charm (then called "Chare Kernel", around 1990) ran on networks of SUN workstations. Our cluster computing research includes:
Portable implementation of parallel programming paradigms on clusters (Converse, Charm++, AMPI, and Java).
Adapting to extraneous loads: In a desktop environment, if one of the workstations being used by a parallel program starts running a desktop job, the performance of the entire parallel application suffers. Our research has led to a system which can detect this situation and readjust the workload accordingly.
Handling machines with different speeds: This is done by using initial speed measurements, and measurement-based load balancing.
In addition to the cluster of SUN workstations in the CS department, and in our lab, we have installed and used:
  • The "Cool: cluster: Intel gave us 64-processor cluster (16 quad xeons). This has been broken into to cluster. The one named "Cool" is our workhorse cluster. The other cluster is being used for Operations Research by Prof. U. S. Palekar.
  • The "Thrift: cluster: A cluster of 8 Linux PCs, put together for under $4,500 in 1998. (This is now being dismantled).
  • In the Theoretical Biophysics collaboration, we had three clusters of 16 HP machines, expanded with another 4 4-processor HP K-boxes, in the Theoretical Biophysics collaboration, since 1993. This was one of the early use of clusters for real applications.
  • Three cluster of Linux machines, in the Theoretical Biophysics Collaboration (Beckman Institute). It consists of 32 processors (16 dual processor boxes) connected by 100 MB ethernet!
  • In addition, we have access to several other clusters, including the "Turing" cluster housed in the Computer Science department (with about 400 processors). This is part of Computational Science and Engineering effort, of which our group is a participant.
Adapting to Load on Workstation Clusters [ Frontiers of Massively Parallel Computation 1999]
Application Performance of a Linux Cluster using Converse [RTSPP 2000]