Essentials of Computer Organization and Architecture
Essentials of Computer Organization and Architecture
Writing efficient programs: performance issues in an undergraduate CS curriculum
Proceedings of the 35th SIGCSE technical symposium on Computer science education
Performance of Runtime Optimization on BLAST
Proceedings of the international symposium on Code generation and optimization
Profiler tools selection for curricular support
Journal of Computing Sciences in Colleges
Computer Architecture, Fourth Edition: A Quantitative Approach
Computer Architecture, Fourth Edition: A Quantitative Approach
Computer Organization and Architecture: Designing for Performance (7th Edition)
Computer Organization and Architecture: Designing for Performance (7th Edition)
Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation)
Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation)
A case study on compiler optimizations for the Intel® Core™ 2 duo processor
International Journal of Parallel Programming
Parallel Programming: for Multicore and Cluster Systems
Parallel Programming: for Multicore and Cluster Systems
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With the increasing availability of multi-core processors, the sequential programming paradigm is no longer capable of harnessing the full power of processors. Parallel programming is however, generally complex and requires more expertise than the traditional sequential programming model. On the other hand, there are a multitude of optimisations for sequential programs that can exploit multiple cores without much effort by the programmer. The primary goal of this research is to identify available tools and techniques to aid programmers in the process of optimising C/C++ programs for execution on multi-processors. Using a couple of example programs we show that improved performance is possible using the proposed methodology. However, the choice of optimisation is dependent on the type of problem being solved and there is no generic best choice for all classes of problems.