Efficient Replacement Policy Research Articles

Improving Performance of a Distributed File System using Hierarchical Collaborative Global Caching Algorithm with Rank-Based Replacement Technique

In the emerging big data scenario, distributed file systems play a vital role for storage and access of large data generated in the web-based information systems. Improving performance of a distributed file system is a very important research issue in the current context. Client side caching and prefetching techniques enhance performance of the distributed file system. Efficient replacement policy is required to improve performance of the caching process. In this paper, we have proposed a novel client side caching algorithm namely hierarchical collaborative global caching algorithm and a cache replacement algorithm namely rank-based cache replacement algorithm. We have used support value computed for the file blocks, for prefetching, caching and replacement purposes. We have proved through simulation experiments that the proposed algorithm performs better than the existing algorithms discussed in the literature.

ROCKY: A Robust Hybrid On-chip Memory Kit For The Processors With STT-MRAM Cache Technology

STT-MRAM is regarded as an extremely promising NVM technology for replacing SRAM-based on-chip memories. While STT-MRAM memories benefit from ultra-low leakage power and high density, they suffer from some reliability challenges, namely, read disturbance, write failure, and retention failure. The write failure; storing a wrong value in an STT-MRAM cell during a write operation, is the most crucial reliability challenge. In this article, we propose ROCKY; a robust architecture equipped with efficient replacement policies for STT-MRAM-based cache memory hierarchy to improve the robustness of STT-MRAM part against the write failures. ROCKY reduces susceptible transitions in STT-MRAM cache memories leading to more reliable STT-MRAM write operations. The simulation results through comparison with traditional cache memory hierarchy demonstrate ROCKY decreases the WER of STT-MRAM cache memories by up to 35.4 percent while imposing less than 1 percent performance overhead to the system.

Split Ways : An Efficient Replacement Policy for Larger Sized Cache Memory

As the data requirement of today’s application is increasing the size of the cache memory in a multicore processor is also increasing. A multicore processor has many levels of cache memory. The Last Level Cache (LLC) is normally shared by all the cores and its size must be large enough to handle today’s data intensive applications. Such larger sized set-associative LLC facing major challenges to efficiently implement the replacement policy of its sets. As the number of ways are increasing in the LLC, the replacement policy becomes a bottleneck of the system. To improve the performance of the system and to reduce the hardware overhead, in this paper we propose a simple but hardware efficient replacement policy for the larger sized LLCs. We call the techniques as SplitWays as it divides (splits) the ways of a set into multiple groups called wayGroups. Each wayGroup maintains its own replacement policy. Experimental analysis using full-system simulator found that the proposed technique reduces the hardware overhead by up to 66% without any performance degradation..

Understanding and Alleviating the Impact of the Flash Address Translation on Solid State Devices

Flash-based solid state devices (SSDs) have been widely employed in consumer and enterprise storage systems. However, the increasing SSD capacity imposes great pressure on performing efficient logical to physical address translation in a page-level flash translation layer (FTL). Existing schemes usually employ a built-in RAM to store mapping information, called mapping cache , to speed up the address translation. Since only a fraction of the mapping table can be cached due to limited cache space, a large number of extra flash accesses are required for cache management and garbage collection, degrading the performance and lifetime of an SSD. In this paper, we first apply analytical models to investigate the key factors that incur extra flash accesses during address translation. Then, we propose a novel page-level FTL with an efficient translation page-level caching mechanism, named TPFTL , to minimize the extra flash accesses. TPFTL employs a two-level least recently used (LRU) list with space-efficient optimizations to organize cached mapping entries. Inspired by the models, we further design a workload-adaptive loading policy combined with an efficient replacement policy to increase the cache hit rate and reduce the writebacks of replaced dirty entries. Finally, we evaluate TPFTL using extensive trace-driven simulations. Our evaluation results show that compared to the state-of-the-art FTLs, TPFTL significantly reduces the extra operations caused by address translation, achieving reductions on system response time and write amplification by up to 27.1% and 32.2%, respectively.

Adaptive Cache Replacement:A Novel Approach

Cache replacement policies are developed to help insure optimal use of limited resources. Varieties of such algorithms exist with relatively few that dynamically adapt to traffic patterns. Algorithms that are tunable typically utilize off-line training mechanisms or trial-and-error to determine optimal characteristics. Utilizing multiple algorithms to establish an efficient replacement policy that dynamically adapts to changes in traffic load and access patterns is a novel option that is introduced in this article. A simulation of this approach utilizing two existing, simple, and effective policies; namely, LRU and LFU was studied to assess the potential of the adaptive policy. This policy is compared and contrasted to other cache replacement policies utilizing public traffic samples mentioned in the literature as well as a synthetic model created from existing samples. Simulation results suggest that the adaptive cache replacement policy is beneficial, primarily in smaller cache sizes.

Optimal renewal policies for complex systems

AbstractMost maintenance and replacement models for industrial equipment have been developed for independent single‐component machines. Most equipment, however, consists of multiple components. Also, when the maintenance crew services several machines, the maintenance policy for each machine is not independent of the states of the other machines.In this paper, two dynamic programming replacement models are presented. The first is used to determine the optimal replacement policy for multi‐component equipment. The second is used to determine the optimal replacement policy for a multi‐machine system which uses one replacement crew to service several machines. In addition, an approach is suggested for developing an efficient replacement policy for a multi‐component, multi‐machine system.