Warp: an integrated solution of high-speed parallel computing
Proceedings of the 1988 ACM/IEEE conference on Supercomputing
Architecture and compiler tradeoffs for a long instruction wordprocessor
ASPLOS III Proceedings of the third international conference on Architectural support for programming languages and operating systems
A parallelizing compiler for distributed memory parallel computers
A parallelizing compiler for distributed memory parallel computers
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PPOPP '93 Proceedings of the fourth ACM SIGPLAN symposium on Principles and practice of parallel programming
Generating communication for array statements: design, implementation, and evaluation
Journal of Parallel and Distributed Computing - Special issue on data parallel algorithms and programming
Supporting systolic and memory communication in iWarp
ISCA '90 Proceedings of the 17th annual international symposium on Computer Architecture
LAPACK Working Note 18: Implementation Guide for LAPACK
LAPACK Working Note 18: Implementation Guide for LAPACK
Automatic generation of systolic programs from nested loops
Automatic generation of systolic programs from nested loops
Switch Design to Enable Predictive Multiplexed Switching in Multiprocessor Networks
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Hi-index | 4.10 |
Distributed-memory parallel systems rely on explicit message exchange for communication, but the communication operations they support can differ in many aspects. One key difference is the way messages are generated or consumed. With systolic communication, a message is transmitted as it is generated. For example, the result computed by the multiplier is sent directly to the communication subsystem for transmission to another node. With memory communication, the complete message is generated and stored in memory, and then transmitted to its destination. Since sender and receiver nodes are individually controlled, they can use different communication styles. One example of memory communication is message passing: both the sender and receiver buffer the message in memory. These two communication styles place different demands on processor design. This article illustrates each style's effect on processor resources for some key application kernels. We are targeting the iWarp system because it supports both communication styles. Two parallel-program generators, one for each communication style, automatically map the sample programs.