多媒体通信任务的组合记忆系统
Compositional Memory Systems for Multimedia Communicating Tasks
摘要：
传统的高速缓存模型不适合实时并行处理，因为任务可能以不可预测的方式将彼此的数据从高速缓存中清除。通过这种方式，系统不是组合的，因此整体性能难以预测，并且新任务的集成成本高昂。本文提出了一种新的方法，对系统的组合性？的性能，使不同的存储层次结构优化可能的多媒体通信任务时，运行在嵌入式多处理器架构。该方法是基于一个高速缓存分配策略，分配集的统一高速缓存专门任务和通信缓冲区。我们还分析制定的问题，并描述了一种方法来计算缓存分区比优化吞吐量和功耗。当应用到多处理器与存储层次结构，我们的技术也提供了性能增益。与共享缓存的情况相比，对于由两个jpeg解码器和一个边缘检测算法组成的应用程序，未命中率减少了5倍，对于mpeg2解码器，未命中率减少了6.5倍。
英文摘要：
Conventional cache models are not suited for real-time parallel processing because tasks may flush each other's data out of the cache in an unpredictable manner. In this way the system is not compositional so the overall performance is difficult to predict and the integration of new tasks expensive. This paper proposes a new method that imposes compositionality to the system?s performance and makes different memory hierarchy optimizations possible for multimedia communicating tasks when running on embedded multiprocessor architectures. The method is based on a cache allocation strategy that assigns sets of the unified cache exclusively to tasks and to the communication buffers. We also analytically formulate the problem and describe a method to compute the cache partitioning ratio for optimizing the throughput and the consumed power. When applied to a multiprocessor with memory hierarchy our technique delivers also performance gain. Compared to the shared cache case, for an application consisting of two jpeg decoders and one edge detection algorithm 5 times less misses are experienced and for an mpeg2 decoder 6.5 times less misses are experienced.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
