Titlebook: Compiling Parallel Loops for High Performance Computers; Partitioning, Data A David E. Hudak,Santosh G. Abraham Book 1993 Springer Science+

ARRAY

書目名稱Compiling Parallel Loops for High Performance Computers影響因子(影響力)




書目名稱Compiling Parallel Loops for High Performance Computers影響因子(影響力)學(xué)科排名




書目名稱Compiling Parallel Loops for High Performance Computers網(wǎng)絡(luò)公開度




書目名稱Compiling Parallel Loops for High Performance Computers網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Compiling Parallel Loops for High Performance Computers被引頻次




書目名稱Compiling Parallel Loops for High Performance Computers被引頻次學(xué)科排名




書目名稱Compiling Parallel Loops for High Performance Computers年度引用




書目名稱Compiling Parallel Loops for High Performance Computers年度引用學(xué)科排名




書目名稱Compiling Parallel Loops for High Performance Computers讀者反饋




書目名稱Compiling Parallel Loops for High Performance Computers讀者反饋學(xué)科排名

龍蝦

https://doi.org/10.1007/978-1-4615-3164-7Contig; Excel; algorithms; architecture; architectures; boundary element method; computer; design; function;

引起痛苦

978-1-4613-6386-6Springer Science+Business Media New York 1993

揉雜

Niels Christian Hvidt,Elisabeth Assing Hvidtn multiprocessor) rely on hundreds of commercially-available microprocessors to provide computing power in a cost-effective manner. Microprocessor architectures and implementations are becoming increasingly sophisticated, e.g., the Alpha microprocessor introduced by Digital Equipment Corporation ope

Commemorate

Spirituality, Religiousness and Healthtain types of parallel loops. Static program partitioning is attractive since the program partition is specified during the compilation phase, thereby eliminating one source of run-time overhead. Furthermore, static partitionings reduce communication overhead relative to dynamic schemes that attempt

嬉耍

嬉耍

https://doi.org/10.1007/978-3-030-02997-5 our analyses to code featuring iterative data-parallel loops and matrix data sets, we have observed several frequently occurring computation structures and communication characteristics. Applications that exhibit various computation structures and communication characteristics are given in Fig. 4.1

蟄伏

Workplace and Organizational Spirituality,ray access methods and loop structures. These methods have been restricted to an analysis of a set of nested data-parallel loops., updating a single global array. In order for these methods to be applicable to a wide range of parallel applications, they must be capable of optimizing multiple data-pa

繼承人

cartilage

Spirituality, Religiousness and HealthD.91] and Stanford DASH multiprocessor systems [LLG.90] have non-uniform access latencies. The increased latency and reduced bandwidth of global memory has a substantial impact on performance. Restructuring of programs can reduce the number of global memory accesses and dramatically improve performance.