Introducing a Data Sliding Mechanism for Cooperative Caching in Manycore Architectures

Abstract

In future micro-architectures, the increase of the number of cores and wire network complexity is leading to several performance degradation. These platforms are intended to process large amount of data. One of the biggest challenges for systems scalability is actually the memory wall: the memory latency is hardly increasing compared to technology expectations. Recent works explore potential software and hardware solutions mainly based on different caching schemes for addressing off-chip access issues.In this paper, we propose a new cooperative caching method improving the cache miss rate for manycore micro-architectures. The work is motivated by some limitations of recent adaptive cooperative caching proposals. Elastic Cooperative caching (ECC), is a dynamic memory partitioning mechanism that allows sharing cache across cooperative nodes according to the application behavior. However, it is mainly limited with cache eviction rate in case of highly stressed neighborhood. Another system, the adaptive Set-Granular Cooperative Caching (ASCC), is based on finer set-based mechanisms for a better adaptability. However, heavy localized cache loads are not efficiently managed. In such a context, we propose a cooperative caching strategy that consists in sliding data through closer neighbors. When a cache receives a storing request of a neighbor's private block, it spills the least recently used private data to a close neighbor. Thus, solicited saturated nodes slide local blocks to their respective neighbors to always provide free cache space. We also propose a new Prioritybased Data Replacement policy to decide efficiently which blocks should be spilled, and a new mechanism to choose host destination called Best Neighbor selector.The first analytic performance evaluation shows that the proposed cache management policies reduce by half the average global communication rate. As frequent accesses are focused in the neighboring zones, it efficiently improves on-Chip traffic.Finally, our evaluation shows that cache miss rate is enhanced: each tile keeps the most frequently accessed data 1-Hop close to it, instead of ejecting them Off-Chip. Proposed techniques notably reduce the cache miss rate in case of high solicitation of the cooperative zone, as it is shown in the performed experiments.

Using the Spring Physical Model to Extend a Cooperative Caching Protocol for Many-Core Processors

“…In a previous work [8], [21], we introduce the data sliding mechanism as a 1-chance forwarding protocol, allowing each core to store its own data in direct neighbors caches.…”

“…But instead, it keeps each block near its owner core. To overcome this, the data sliding mechanism [8] has been proposed. The main motivation of this prior work was to enhance both cache partitioning and data sliding techniques in order to effectively manage highly stressed neighborhoods.…”

“…In a previous work [8], we proposed an extension of the ECC system, called the data sliding mechanism. It allows a core to store a data onto a neighbor, even if this neighbor is stressed by a hot-spot.…”