No abstract

A modern computer system provides its support via system software that consists of applications such as an assembler, a linker, a loader and virtual machines. It is of prime importance to give students that are learning system‐software concepts a solid base of knowledge without any unnecessary details. To make the subject easy to understand we designed a simulator for a hypothetical computer that is already used in several courses on system software. In the paper, we describe the simulator's behavior as well as its design and implementation. Additionally, we present three case studies of using a simulator in teaching and describe our experience of its use in a course on system software. From the experience of using the simulator in a pedagogical process we conclude that it decreases the time invested by the students to comprehend the topic, and at the same time it enables in depth understanding. © 2013 Wiley Periodicals, Inc. Comput Appl Eng Educ 23:137–146, 2015; View this article online at http://wileyonlinelibrary.com/journal/cae; DOI

No abstract

Abstract:In recent years, graphics processing units (GPU) have become a standard part of high-performance computing systems used for solving large scale computation problems. To relieve the main processor more and more time consumptive tasks are moved from CPU to GPU where algorithms run in parallel on a high number of GPU's processors. In this paper we present both sequential and parallel implementations of a simple matrix multiplication algorithm and we compare the overall execution time. To further speed up the execution we introduce the GPU's fast shared memory and the implementation of the matrix multiplication algorithm that exploits this memory. The results presented in this paper show that the GPU implementation with the use of shared memory is two times faster than the implementation that uses only device's global memory and up to 7.5 times faster than the CPU implementation.

No abstract