While accelerators have become more prevalent in recent years, they are still considered hard to program. In this work, we extend a framework for parallel programming so that programmers can easily take advantage of the Cell processor's Synergistic Processing Elements (SPEs) as seamlessly as possible. Using this framework, the same application code can be compiled and executed on multiple platforms, including x86-based and Cell-based clusters. Furthermore, our model allows independently developed libraries to efficiently time-share one or more SPEs by interleaving work from multiple libraries. To demonstrate the framework, we present performance data for an example molecular dynamics (MD) application. When compared to a single Xeon core utilizing streaming SIMD extensions (SSE), the MD program achieves a speedup of 5.74 on a single Cell chip (with 8 SPEs). In comparison, a similar speedup of 5.89 is achieved using six Xeon (x86) cores.

While the Cell processor, jointly developed by IBM, Sony, and Toshiba, has great computational power, it also presents many challenges including portability and ease of programming. We have been adapting the Charm++ Runtime System to utilize the Cell. We believe that the Charm++ model fits well with the Cell for many reasons: encapsulation of data, effective prefetching, the ability to peak ahead in message queues, virtualization, etc. To these ends, we have developed the Offload API (an independent code) which allows Charm++ applications to easily take advantage of the Cell. Our goal is to allow Charm++ programs to run on Cell-based and non-Cell-based platforms without modification to application code. Example Charm++ programs using the Offload API already exist. We have also begun modifying NAMD, a popular molecular dynamics code, to use the Cell. In this poster, we plan to present current progress and future plans for this work.