Estimating interlock and improving balance for pipelined architectures
Journal of Parallel and Distributed Computing
Proceedings of the 1993 ACM/IEEE conference on Supercomputing
Scalable load balancing techniques for parallel computers
Journal of Parallel and Distributed Computing
Scalability issues affecting the design of a dense linear algebra library
Journal of Parallel and Distributed Computing - Special issue on scalability of parallel algorithms and architectures
High performance software on Intel Pentium Pro processors or Micro-Ops to TeraFLOPS
SC '97 Proceedings of the 1997 ACM/IEEE conference on Supercomputing
Measurement of Communication Rates on the Cray T3D Interprocessor Network
HPCN Europe 1994 Proceedings of the nternational Conference and Exhibition on High-Performance Computing and Networking Volume II: Networking and Tools
A note on scaling the Linpack benchmark
Journal of Parallel and Distributed Computing
Paper: Performance parameters and benchmarking of supercomputers
Parallel Computing
Dimensional analysis applied to a parallel QR algorithm
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Computational forces in the SAGE benchmark
Journal of Parallel and Distributed Computing
Self-similarity of parallel machines
Parallel Computing
Computer performance analysis and the Pi Theorem
Computer Science - Research and Development
Hi-index | 0.00 |
Dimensional analysis reduces a complicated ten-parameter formula for the execution time of the Linpack benchmark to a simpler two-parameter formula. These two parameters are ratios of software forces and hardware forces that determine a self-similarity surface. Machines move along paths on this surface as the problem size and the number of processors change. Two machines scale the same way, they move along the same path, if they have the same hardware forces. To design efficient algorithms, the programmer must produce software forces large enough to overcome the hardware forces. Modern machines have larger hardware forces than older machines and are harder to program.