Sam broadcaster pro 2015.1 key8/5/2023 However, several factors, such as unique architecture of GPU, rise of CPU–GPU heterogeneous computing, etc., demand effective management of caches to achieve high performance and energy efficiency. To address the requirements of these applications, modern GPUs include sizable hardware- managed caches. Initially introduced as special-purpose accelerators for graphics applications, graphics processing units (GPUs) have now emerged as general purpose computing platforms for a wide range of applications. ![]() These experiments show that WATCHMAN achieves a substantial performance improvement in a decision support environment when compared to a traditional LRU replacement algorithm.Ī Survey Of Techniques for Managing and Leveraging Caches in GPUs We report on a performance evaluation based on the TPC-D and Set Query benchmarks. The cache replacement and admission algorithms make use of a profit metric, which considers for each retrieved set its average rate of reference, its size, and execution cost of the associated query. WATCHMAN aims at minimizing query response time and its cache replacement policy swaps out entire retrieved sets of queries instead of individual pages. Our cache manager employs two novel, complementary algorithms for cache replacement and for cache admission. In this paper we report on the design of an intelligent cache manager for sets retrieved by queries called WATCHMAN, which is particularly well suited for data warehousing environment. Because data warehouses are updated infrequently, it becomes possible to improve query performance by caching sets retrieved by queries in addition to query execution plans. Query performance in such an environment is critical because decision support applications often require interactive query response time. Such applications involve complex queries. ![]() Scheuermann, Peter Shim, Junho Vingralek, Radekĭata warehouses store large volumes of data which are used frequently by decision support applications. WATCHMAN: A Data Warehouse Intelligent Cache Manager We evaluate Pro Cache and conclude that it achieves comparable performance compared to a more complex reference counter-based cache-management scheme. Owing to its simplicity, Pro Cache is easy to implement at a substantially smaller cost than similar previously studied techniques. Our scheme is motivated by the observation that frequently written hot data will eventually enter the cache with a high probability, and that infrequently accessed cold data will not enter the cache easily. In this paper, we propose and study Pro Cache, a simple NVM cache management scheme, that makes cache-entrance decisions based on random probability testing. To maximize the benefits of an NVM cache, it is important to increase the NVM cache utilization. Absorbing small writes in a fast NVM cache can also reduce the number of flash memory erase operations. To solve this problem, a fast non-volatile memory (NVM-)based cache has been employed within SSDs to reduce the long latency required to write data. However, as the flash memory stores more bits per cell, the performance and reliability of the flash memory degrade substantially. Solid-state drives (SSDs) have recently become a common storage component in computer systems, and they are fueled by continued bit cost reductions achieved with smaller feature sizes and multiple-level cell technologies. We evaluate Pro Cache and conclude that it achieves comparable performance compared to a more complex reference counter-based cache-management scheme.ĭon’t make cache too complex: A simple probability-based cache management scheme for SSDs Don't make cache too complex: A simple probability-based cache management scheme for SSDs.īaek, Seungjae Cho, Sangyeun Choi, Jongmoo
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