Smart Cache

About: Smart Cache is a research topic. Over the lifetime, 7680 publications have been published within this topic receiving 180618 citations.

Hierarchical Coded Caching

Abstract: caching of popular content during off-peak hours is a strategy to reduce network loads during peak hours. Recent work has shown significant benefits of designing such caching strategies not only to locally deliver the part of the content, but also to provide coded multicasting opportunities even among users with different demands. Exploiting both of these gains was shown to be approximately optimal for caching systems with a single layer of caches. Motivated by practical scenarios, we consider, in this paper, a hierarchical content delivery network with two layers of caches. We propose a new caching scheme that combines two basic approaches. The first approach provides coded multicasting opportunities within each layer; the second approach provides coded multicasting opportunities across multiple layers. By striking the right balance between these two approaches, we show that the proposed scheme achieves the optimal communication rates to within a constant multiplicative and additive gap. We further show that there is no tension between the rates in each of the two layers up to the aforementioned gap. Thus, both the layers can simultaneously operate at approximately the minimum rate.

Web cache performance by applying different replacement policies to the web cache

Abstract: A cache system is described that includes a storage that is partitioned into a plurality of storage areas, each for storing one kind of objects received from remote sites and to be directed to target devices. The cache system further includes a cache manager coupled to the storage to cause objects to be stored in the corresponding storage areas of the storage. The cache manager causes cached objects in each of the storage areas to be replaced in accordance with one of a plurality of replacement policies, each being optimized for one kind of objects.

MPC: Popularity-based caching strategy for content centric networks

Abstract: Content Centric Networking (CCN) has recently emerged as a promising architecture to deliver content at large-scale. It is based on named-data where a packet address names content and not its location. Then, the premise is to cache content on the network nodes along the delivery path. An important feature for CCN is therefore to manage the cache of the nodes. In this paper, we present Most Popular Content (MPC), a new caching strategy adapted to CCN networks. By caching only popular content, we show through extensive simulation experiments that MPC is able to cache less content while, at the same time, it still achieves a higher Cache Hit and outperforms existing default caching strategy in CCN.

Cache bursts: A new approach for eliminating dead blocks and increasing cache efficiency

Abstract: Data caches in general-purpose microprocessors often contain mostly dead blocks and are thus used inefficiently. To improve cache efficiency, dead blocks should be identified and evicted early. Prior schemes predict the death of a block immediately after it is accessed; however, these schemes yield lower prediction accuracy and coverage. Instead, we find that predicting the death of a block when it just moves out of the MRU position gives the best tradeoff between timeliness and prediction accuracy/coverage. Furthermore, the individual reference history of a block in the L1 cache can be irregular because of data/control dependence. This paper proposes a new class of dead-block predictors that predict dead blocks based on bursts of accesses to a cache block. A cache burst begins when a block becomes MRU and ends when it becomes non-MRU. Cache bursts are more predictable than individual references because they hide the irregularity of individual references. When used at the L1 cache, the best burst-based predictor can identify 96% of the dead blocks with a 96% accuracy. With the improved dead-block predictors, we evaluate three ways to increase cache efficiency by eliminating dead blocks early: replacement optimization, bypassing, and prefetching. The most effective approach, prefetching into dead blocks, increases the average L1 efficiency from 8% to 17% and the L2 efficiency from 17% to 27%. This increased cache efficiency translates into higher overall performance: prefetching into dead blocks outperforms the same prefetch scheme without dead-block prediction by 12% at the L1 and by 13% at the L2.

Frequent value compression in data caches

Abstract: Since the area occupied by cache memories on processor chips continues to grow, an increasing percentage of power is consumed by memory. We present the design and evaluation of the compression cache (CC) which is a first level cache that has been designed so that each cache line can either hold one uncompressed line or two cache lines which have been compressed to at least half their lengths. We use a novel data compression scheme based upon encoding of a small number of valves that appear frequently during memory accesses. This compression scheme preserves the ability to randomly access individual data items. We observed that the contents of 40%, 52% and 51% of the memory blocks of size 4, 8, and 16 words respectively in SPECint95 benchmarks can be compressed to at least half their sizes by encoding the top 2, 4, and 8 frequent valves respectively. Compression allows greater amounts of data to be stored leading to substantial reductions in miss rates (0-36.4%), off-chip traffic (3.9-48.1%), and energy consumed (1-27%). Traffic and energy reductions are in part derived by transferring data over external buses in compressed form.