
Special challenges exist in writing reliable numerical library software for heterogeneous computing environments. Although a lot of software for distributed-memory parallel computers has been written, porting this software to a network of workstations requires careful consideration. The symptoms of heterogeneous computing failures can range from erroneous results without warning to deadlock. Some of the problems are straightforward to solve, but for others the solutions are not so obvious, or incur an unacceptable overhead. Making software robust on heterogeneous systems often requires additional communication. We describe and illustrate the problems encountered during the development of ScaLAPACK and the NAG Numerical PVM Library. Where possible, we suggest ways to avoid potential pitfalls, or if that is not possible, we recommend that the software not be used on heterogeneous networks.
Network design and communication in computer systems, Parallel algorithms, Floating-point arithmetic, Distributed-memory systems, Reliability, heterogeneous computing, D.1.3 [Programming Techniques]: Concurrent Programming - distributed programming, G.1.0 [Numerical Analysis]: General - computer arithmetic, Algorithms
Network design and communication in computer systems, Parallel algorithms, Floating-point arithmetic, Distributed-memory systems, Reliability, heterogeneous computing, D.1.3 [Programming Techniques]: Concurrent Programming - distributed programming, G.1.0 [Numerical Analysis]: General - computer arithmetic, Algorithms
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