SPARSE MATRIX MULTIPLICATION ON VECTOR COMPUTERS
نویسندگان
چکیده
منابع مشابه
Reconfigurable Sparse Matrix-Vector Multiplication on FPGAs
executing memory-intensive simulations, such as those required for sparse matrix-vector multiplication. This effect is due to the memory bottleneck that is encountered with large arrays that must be stored in dynamic RAM. An FPGA core designed for a target performance that does not unnecessarily exceed the memory imposed bottleneck can be distributed, along with multiple memory interfaces, into...
متن کاملOptimizing Sparse Matrix Vector Multiplication on SMPs
We describe optimizations of sparse matrix-vector multiplication on uniprocessors and SMPs. The optimization techniques include register blocking, cache blocking, and matrix reordering. We focus on optimizations that improve performance on SMPs, in particular, matrix reordering implemented using two diierent graph algorithms. We present a performance study of this algorithmic kernel, showing ho...
متن کاملSparse Matrix-Vector Multiplication on FPGAs
Floating-point Sparse Matrix-Vector Multiplication (SpMXV) is a key computational kernel in scientic and engineering applications. The poor data locality of sparse matrices signicantly reduces the performance of SpMXV on general-purpose processors, which rely heavily on the cache hierarchy to achieve high performance. The abundant hardware resources on current FPGAs provide new opportunities to...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of High Speed Computing
سال: 1990
ISSN: 0129-0533
DOI: 10.1142/s012905339000008x