Affiliation:
1. IRISA 35042 Rennes Cedex, France
Abstract
The goal of the Pandore system is to allow the execution of parallel algorithms on DMPCs (Distributed Memory Parallel Computers) without having to take into account the low-level characteristics of the target distributed computer to program the algorithm. No explicit process definition and interprocess communications are needed. Parallelization is achieved through logical data organization. The Pandore system provides the user with a mean to specify data partitioning and data distribution over a domain of virtual processors for each parallel step of his algorithm.
At compile time, Pandore splits the original program into parallel processes. Each process will execute some appropriate parts of the original code, according to the given data decomposition. In order to achieve a correct utilization of the data structures distributed over the processors, the Pandore system provides an execution scheme based on a communication layer, which is an abstraction of a message-passing architecture. This intermediate level is them implemented using the effective primitives of the real architecture (in our specific case, an Intel iPSC/2).
Publisher
Association for Computing Machinery (ACM)
Reference6 articles.
1. Distributed data structures in Linda
2. Hans P. Zima Heinz-J. Bast and Michael Gerndt. SUPERB' a tool for semi-automatic MIMD/SIMD parallelization. Parallel Computing (6):1-18 1988. Hans P. Zima Heinz-J. Bast and Michael Gerndt. SUPERB' a tool for semi-automatic MIMD/SIMD parallelization. Parallel Computing (6):1-18 1988.
3. Matthew Rossing robert B. Schnabel and Robert Weaver. Dino" summary and examples. In 3' Conference on Hypercubes Concurrent Computers and Applications pages 472-481 1988. 10.1145/62297.62353 Matthew Rossing robert B. Schnabel and Robert Weaver. Dino" summary and examples. In 3' Conference on Hypercubes Concurrent Computers and Applications pages 472-481 1988. 10.1145/62297.62353
4. Process decomposition through locality of reference