
doi: 10.1109/pdp.2014.16
handle: 2268/207180
Data are traditionally represented using native format such as integer or floating-point numbers in various flavor. However, some applications rely on more complex representation format. This is the case when uncertainty needs to be apprehended. Fuzzy arithmetic is one of the major tools to address this problem, but the execution time of basic operations such as addition or multiplication makes its usage prohibitive. In this article, thanks to a new representation format and modern GPU characteristics we show that it is possible to greatly reduce the execution time of those operations. These techniques have been implemented in fuzzyGPU, a freely distributed library of common operations over fuzzy number.
Sciences informatiques, computer arithmetic, [INFO.INFO-AR] Computer Science [cs]/Hardware Architecture [cs.AR], GPGPU, [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], [INFO.INFO-AO] Computer Science [cs]/Computer Arithmetic, Computer science, Fuzzy arithmetic, Engineering, computing & technology, Ingénierie, informatique & technologie
Sciences informatiques, computer arithmetic, [INFO.INFO-AR] Computer Science [cs]/Hardware Architecture [cs.AR], GPGPU, [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], [INFO.INFO-AO] Computer Science [cs]/Computer Arithmetic, Computer science, Fuzzy arithmetic, Engineering, computing & technology, Ingénierie, informatique & technologie
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