<title>Synthesizing parallel imaging applications using the CAP (computer-aided parallelization) tool</title>

Abstract

Imaging applications such as filtering, image transforms and compression/decompression require vast amounts of cornputing power when applied to large data sets. These applications would potentially benefit from the use of parallel processing. However, dedicated parallel computers are expensive and their processing power per node lags behind that of the most recent commodity components. Furthermore, developing parallel applications remains a difficult task : writing and debugging the application is difficult (deadlocks), programs may not be portable from one parallel architecture to the other, and performance often comes short of expectations.In order to facilitate the development of parallel applications, we propose the CAP computer-aided parallelization tool which enables application programmers to specify at a high-level of abstraction the flow of data between pipelined-parallel operations. In addition, the CAP tool supports the programmer in developing parallel imaging and storage operations. CAP enables combining efficiently parallel storage access routines and image processing sequential operations. This paper shows how processing and I/O intensive imaging applications must be implemented to take advantage of parallelism and pipelining between data access and processing. This paper's contribution is (1) to show how such implementations can be compactly specified in CAP, and (2) to demonstrate that CAP specified applications achieve the performance of custom parallel code. The paper analyzes theoretically the performance of CAP specified applications and demonstrates the accuracy of the theoretical analysis through experimental measurements.

<title>Computer-aided synthesis of parallel image processing applications</title>

“…Besides the Visible Human Slice Server, CAP has been applied successfully to a number of applications, both in the field of image processing 4 and in the field scientific computing 3,7 . We have shown 3 that the overhead specific to CAP is very low: each token incorporates in addition to its user-defined structure a 24 bytes header.…”

Armada: a parallel I/O framework for computational grids

“…PS 2 is a data-flow system that uses the computer-aided parallelization tool (CAP) [32] to express the parallel behavior of the I/O intensive applications at a high-level. The CAP system constructs a data-flow computation graph with "actors" as nodes of the graph.…”