A fuzzy replacement algorithm (FRA) for cache memories has been proposed (Hossain et al., 1991). In this paper we present a modified fuzzy replacement algorithm (MFRA) that improves the performance of the cache
A replacement algorithm based on fuzzy logic for set associative cache memories was proposed earlier. An effective hardware implementation for the fuzzy replacement algorithm will be presented here. The hardware is based on the use of field-programmable gate arrays (FPGAs). These devices combine the...
In the case in which there is still a tie among cache sectors, the sector to be replaced may be randomly selected among such cache sectors. Unlike conventional sectored cache replacement algorithms, the improved algorithm implemented by the method and computer program product accounts for both hit...
Cache memory is the fast memory which is used to conduit the speed difference of memory and processor. The access patterns of Level 1 cache (L1) and Level 2 cache (L2) are different, when CPU not gets the desired data in L1 then it accesses L2. Thus the replacement algorithm which ...
Partitioned replacement for cache memory.In a particular embodiment, a circuit device includes a translation look-aside buffer (TLB) configured to receive a virtual address and to translate the virtual address to a physical address of a cache having at least two partitions. The circuit device also...
with least value is chosen for replacement. Traditional cache replacement policies like Least Recently Used (LRU) and Least Frequently Used (LFU) use only one parameter to make the replacement decision. LRU is the most common replacement algorithm used in this method (Stann and Heidemann, 2003)...
However, in a multi-threaded processor that includes a shared cache, each thread may have access to the cache memory and each thread may experience cache misses that result in a new data item being loaded into the cache memory. Such replacements can result in deletion of data or instructions...
Spark does not have a good mechanism toselect reasonable RDDs to cachetheir partitions in limited memory. --> Propose a novel selection algorithm,by which Spark can automatically select the RDDs to cache their partitions in memoryaccording to the number of use for RDDs. --> speeds up iterat...
Matrix multiplication is compute intensive, memory demand and cache intensive algorithm. It performs O ( N 3 ) operations, demands storing O ( N 2 ) elements and accesses O ( N ) times each element, where N is the matrix size. Implementation of cache intensive algorithms can achieve ...
In this paper we formulate this problem – giving cache hints to memory instructions such that cache miss rate is minimized – as a0/1 knapsack problem, which can be efficiently solved using adynamic programming algorithm. The proposed approach has been implemented in our compiler testbed and ...