DocumentCode
2160246
Title
A massively parallel multithreaded architecture: DAVRID
Author
Ha, Sangho ; Kim, Junghwan ; Rho, Eunha ; Nah, Yoonhee ; Han, Sangyong ; Hwang, Daejoon ; Kim, Heunghwan ; Cho, Seungho
Author_Institution
Dept. of Comput. Sci. & Stat., Seoul Nat. Univ., South Korea
fYear
1994
fDate
10-12 Oct 1994
Firstpage
70
Lastpage
74
Abstract
MPAs (massively parallel architectures) should address two fundamental issues for scalability: synchronization and communication latency. Dataflow architectures cause problems of excessive synchronization costs and inefficient execution of sequential programs while they offer the ability to exploit massive parallelism inherent in programs. In contrast, MPAs based on the von Neumann computational model may suffer from inefficient synchronization mechanism and communication latencies. DAVRID (Dataflow von Neumann, RISC Hybrid) is a massively parallel multithreaded architecture. By combining the advantages of the von Neumann model and the dataflow model, DAVRID preserves good single thread performance and tolerates latency and synchronization costs. We describe the DAVRID architecture and evaluate it through simulation results over several benchmarks
Keywords
instruction sets; parallel architectures; parallel processing; parallel programming; reduced instruction set computing; synchronisation; DAVRID; Dataflow von Neumann RISC Hybrid; MPAs; communication latency; dataflow architectures; massive parallelism; massively parallel multithreaded architecture; scalability; sequential programs; single thread performance; synchronization; von Neumann computational model; Computer architecture; Computer science; Contracts; Costs; Data engineering; Delay; Processor scheduling; Registers; Scalability; Yarn;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Design: VLSI in Computers and Processors, 1994. ICCD '94. Proceedings., IEEE International Conference on
Conference_Location
Cambridge, MA
Print_ISBN
0-8186-6565-3
Type
conf
DOI
10.1109/ICCD.1994.331857
Filename
331857
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