scholarly journals L2 cache performance analysis for MPSoC by tag – comparision

2017 ◽  
Vol 7 (1.5) ◽  
pp. 285
Author(s):  
Jenitha A ◽  
Elumalai R

Memory systems in many applications are becoming increasingly large, contributing to many challenges in the memory management that has led to many method to manage memory. The tag comparison consumes large amount of cache energy. Current methods provide tag comparison cache or failure of the expected cache. Here is proposed an idea based on new call Comparing Tag stages, filter bloom is presented to improve the efficiency of the cache to predict failure and partial tag comparison for the cold line of verification and full comparison check for direct labels. Moreover, the administration of the cache that is filled with cache lines occurs when there is a cache miss. Today's embedded applications use MPSoC. The  MPSoC consists of the following ie more than one  processors, shared memory among the processors available and a global  off-chip memory. Planning of the activities of an integrated application processor and memory partition between processors are two main critical problem. Here, for an integrated application, both task scheduling and partitioning the integrated available L2 cache to reduce the runtime approach is used.

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Shaily Mittal ◽  
Nitin

Nowadays, Multiprocessor System-on-Chip (MPSoC) architectures are mainly focused on by manufacturers to provide increased concurrency, instead of increased clock speed, for embedded systems. However, managing concurrency is a tough task. Hence, one major issue is to synchronize concurrent accesses to shared memory. An important characteristic of any system design process is memory configuration and data flow management. Although, it is very important to select a correct memory configuration, it might be equally imperative to choreograph the data flow between various levels of memory in an optimal manner. Memory map is a multiprocessor simulator to choreograph data flow in individual caches of multiple processors and shared memory systems. This simulator allows user to specify cache reconfigurations and number of processors within the application program and evaluates cache miss and hit rate for each configuration phase taking into account reconfiguration costs. The code is open source and in java.


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