Solving problems on concurrent processors. Vol. 1: General techniques and regular problems
Solving problems on concurrent processors. Vol. 1: General techniques and regular problems
Introduction to parallel computing: design and analysis of algorithms
Introduction to parallel computing: design and analysis of algorithms
A static parameter based performance prediction tool for parallel programs
ICS '93 Proceedings of the 7th international conference on Supercomputing
An integrated compilation and performance analysis environment for data parallel programs
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
A Unified Framework for Optimizing Communication in Data-Parallel Programs
IEEE Transactions on Parallel and Distributed Systems
Automatic Performance Prediction of Parallel Programs
Automatic Performance Prediction of Parallel Programs
Performance Metrics: Keeping the Focus on Runtime
IEEE Parallel & Distributed Technology: Systems & Technology
Performance Prediction: A Case Study Using a Scalable Shared-Virtual-Memory Machine
IEEE Parallel & Distributed Technology: Systems & Technology
Scalability of Parallel Algorithm-Machine Combinations
IEEE Transactions on Parallel and Distributed Systems
Performance Considerations of Shared Virtual Memory Machines
IEEE Transactions on Parallel and Distributed Systems
The Relation of Scalability and Execution Time
IPPS '96 Proceedings of the 10th International Parallel Processing Symposium
A communication placement framework with unified dependence and data-flow analysis
HIPC '96 Proceedings of the Third International Conference on High-Performance Computing (HiPC '96)
Buffer-Safe Communication Optimization based on Data Flow Analysis and Performance Prediction
PACT '97 Proceedings of the 1997 International Conference on Parallel Architectures and Compilation Techniques
Computer
Execution-driven performance analysis for distributed and parallel systems
Proceedings of the 2nd international workshop on Software and performance
Scalability versus execution time in scalable systems
Journal of Parallel and Distributed Computing
PDRS: A Performance Data Representation System
IPDPS '00 Proceedings of the 15 IPDPS 2000 Workshops on Parallel and Distributed Processing
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A major difficulty in restructuring compilation, and in parallel programming in general, is how to compare parallel performance over a range of system and problem sizes. Execution time varies with system and problem size and an initially fast implementation may become slow when system and problem size scale up. This paper introduces the concept of range comparison. Unlike conventional execution time comparison in which performance is compared for a particular system and problem size, range comparison compares the performance of programs over a range of ensemble and problem sizes via scalability and performance crossing point analysis. A novel algorithm is developed to predict the crossing point automatically. The correctness of the algorithm is proven and a methodology is developed to integrate range comparison into restructuring compilations for data-parallel programming. A preliminary prototype of the methodology is implemented and tested under Vienna Fortran Compilation System. Experimental results demonstrate that range comparison is feasible and effective. It is an important asset for program evaluation, restructuring compilation, and parallel programming.