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| Content Provider | ACM Digital Library |
|---|---|
| Author | Defour, David Milano, Federico Marin, Manuel |
| Copyright Year | 2016 |
| Description | Author Affiliation: University of Perpignan Via Domitia, Perpignan cedex, France(University college dublin, Dublin, Ireland (Milano, Federico; University of liège, Liège, Belgium (Marin, Manuel); Defour, David)) |
| Abstract | This article addresses the execution cost of arithmetic operations with a focus on fuzzy arithmetic. Thanks to an appropriate representation format for fuzzy intervals, we show that it is possible to halve the number of operations and divide by 2 to 8 the memory requirements compared to conventional solutions. In addition, we demonstrate the benefit of some hardware features encountered in today’s accelerators (GPU) such as static rounding, memory usage, instruction-level parallelism (ILP), and thread-level parallelism (TLP). We then describe a library of fuzzy arithmetic operations written in CUDA and C++. The library is evaluated against traditional approaches using compute-bound and memory-bound benchmarks on Nvidia GPUs, with an observed performance gain of 2 to 20. |
| Starting Page | 1 |
| Ending Page | 22 |
| Page Count | 22 |
| File Format | |
| ISSN | 00983500 |
| e-ISSN | 15577295 |
| DOI | 10.1145/2939364 |
| Volume Number | 43 |
| Issue Number | 3 |
| Journal | ACM Transactions on Mathematical Software (TOMS) |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-12-05 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Fuzzy intervals Graphic processing units Lower-upper Midpoint-radius |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Software |
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