图形处理单元的多精度BLAS库

K. Isupov, V. Knyazkov
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引用次数: 7

摘要

binary32和binary64浮点格式在当前硬件上提供了良好的性能,但也在几乎每个算术运算中引入了舍入误差。因此,在大型计算中,舍入误差的累积可能导致准确性问题。防止这些问题的一种方法是使用多精度浮点运算。这份预印本提交给2020年俄罗斯超级计算日,展示了一个新的基本线性代数运算库,用于图形处理单元,具有多种精度。该库是用CUDA C/ c++编写的,并使用剩余数系统来表示浮点数的多精度有效位数。考虑了支持的数据类型、内存布局和库的主要特性。实验结果显示了该库的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiple-Precision BLAS Library for Graphics Processing Units
The binary32 and binary64 floating-point formats provide good performance on current hardware, but also introduce a rounding error in almost every arithmetic operation. Consequently, the accumulation of rounding errors in large computations can cause accuracy issues. One way to prevent these issues is to use multiple-precision floating-point arithmetic. This preprint, submitted to Russian Supercomputing Days 2020, presents a new library of basic linear algebra operations with multiple precision for graphics processing units. The library is written in CUDA C/C++ and uses the residue number system to represent multiple-precision significands of floating-point numbers. The supported data types, memory layout, and main features of the library are considered. Experimental results are presented showing the performance of the library.
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