Abstract:The improvement in performance gained by the use of a multi core processor depends very much on the software algorithms used and their implementation. In particular, possible gains are limited by the fraction of the software that can be run in parallel simultaneously on multiple cores and this effect is described by Amdahl's law. Most applications, however, are not accelerated so much unless programmers invest a prohibitive amount of effort in refactoring the whole problem. In order to exploit the complete capabilities of multi core systems, applications have to become increasingly parallel in nature. Writing parallel program is not an easy task. OpenMP programming model helps in creating multithreaded applications for the existing sequential programs. This paper analyses the performance improvement of a parallel algorithm on multi core systems. The experimental results shows Significant speed up achieved on multi core systems with the parallel algorithm.

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As chip multiprocessors (CMP) have become eminent in all areas of computing, it is inevitable for the operating system to schedule processes efficiently on different cores. These multi-cores pose different challenges of which shared resource contention is the dominant one, as cores share resources like last level cache (LLC) and main memory. This can lead to poor and unpredictable performance of the threads running on the system. The cache replacement policy of LLC becomes critical in managing the cache data in an efficient way. Though prominent, least recently used (LRU) algorithm has some issues with applications which do not follow the temporal locality pattern. This study proposes a modification to the LRU algorithm where a random selection of the victim from 'N' LRU blocks yields better results than the conventional method. The evaluation of the algorithm is carried out using Multi2sim simulator using Parsec and Splash2 benchmarks. The results show an overall performance improvement in hit ratio up to 6% and 2% over LRU for PARSEC and SPLASH2 benchmarks respectively.

As chip multiprocessors (CMP) have become eminent in all areas of computing, it is inevitable for the operating system to schedule processes efficiently on different cores. These multi-cores pose different challenges of which shared resource contention is the dominant one, as cores share resources like last level cache (LLC) and main memory. This can lead to poor and unpredictable performance of the threads running on the system. The cache replacement policy of LLC becomes critical in managing the cache data in an efficient way. Though prominent, least recently used (LRU) algorithm has some issues with applications which do not follow the temporal locality pattern. This study proposes a modification to the LRU algorithm where a random selection of the victim from 'N' LRU blocks yields better results than the conventional method. The evaluation of the algorithm is carried out using Multi2sim simulator using Parsec and Splash2 benchmarks. The results show an overall performance improvement in hit ratio up to 6% and 2% over LRU for PARSEC and SPLASH2 benchmarks respectively.

No abstract