Evaluating the soft error sensitivity of a GPU-based SoC for matrix multiplication

On-line soft error correction in matrix-matrix multiplication

Soft errors are one-time events that corrupt the state of a computing system but not its overall functionality. Soft errors normally do not interrupt the execution of the affected program, but the affected computation results cannot be trusted any more. A well known technique to correct soft errors in matrix–matrix multiplication is algorithm-based fault tolerance (ABFT). While ABFT achieves mu...

Sparse Matrix-Vector Multiplication on a GPU

Matrix-matrix Multiplication in Matlab Using the Gpu

The use of GPU’s as the main computing resource has yielded great speed-up factors in several fields including solving differential equations, linear algebra, signal processing and database queries. There have been several attempts at implementing efficient algorithms for matrix-matrix products with varying results. In-depth analysis of the algorithms has been presented as well. In this paper I...

Optimizing Sparse Matrix-vector Multiplication Based on Gpu

In recent years, Graphics Processing Units(GPUs) have attracted the attention of many application developers as powerful massively parallel system. Computer Unified Device Architecture (CUDA) as a general purpose parallel computing architecture makes GPUs an appealing choice to solve many complex computational problems in a more efficient way. Sparse Matrix-vector Multiplication(SpMV) algorithm...

developing a pattern based on speech acts and language functions for developing materials for the course “ the study of islamic texts translation”

هدف پژوهش حاضر ارائه ی الگویی بر اساس کنش گفتار و کارکرد زبان برای تدوین مطالب درس "بررسی آثار ترجمه شده ی اسلامی" می باشد. در الگوی جدید، جهت تدوین مطالب بهتر و جذاب تر، بر خلاف کتاب-های موجود، از مدل های سطوح گفتارِ آستین (1962)، گروه بندی عملکردهای گفتارِ سرل (1976) و کارکرد زبانیِ هالیدی (1978) بهره جسته شده است. برای این منظور، 57 آیه ی شریفه، به صورت تصادفی از بخش-های مختلف قرآن انتخاب گردید...