Name
Abstract | ||
|---|---|---|
Instruction level parallelism(ILP) is strictly limited by various dependencies. In particular , data dependency is the major performance bottleneck of data intensive applications. To accelerate the execution of sequential code serialized due to data dependencies, this paper proposes an imprecise computation as a fast data computing technique for a high-performance asynchronous processor. To show the performance benefits of the suggested computing model, simulation results are presented. The imprecise computation can be used effectively in data intensive processing with a microprocessor, a Digital Signal Processor or a multimedia processor. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1145/370155.370342 | ASP-DAC |
Keywords | Field | DocType |
imprecise computation,performance benefit,major performance bottleneck,imprecise data computation,data intensive application,data intensive processing,suggested computing model,data dependency,high performance asynchronous processor,multimedia processor,fast data,high-performance asynchronous processor,computer architecture,instruction level parallelism,computational modeling,high performance computing,instruction sets,concurrent computing,digital signal processor,computer model,real time systems | Instruction-level parallelism,Asynchronous communication,Bottleneck,Data dependency,Supercomputer,Digital signal processor,Computer science,Instruction set,Parallel computing,Real-time computing,Concurrent computing | Conference |
ISBN | Citations | PageRank |
0-7803-6634-4 | 1 | 0.36 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jeong-Gun Lee | 1 | 72 | 18.27 |
| Euiseok Kim | 2 | 46 | 10.09 |
| Dongik Lee | 3 | 77 | 14.46 |