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.

The discrepancy between Planck data and direct measurements of the current expansion rate H0 and the matter fluctuation amplitude S8 has become one of the most intriguing puzzles in cosmology nowadays. The H0 tension has reached 4.2σ in the context of standard cosmology i.e ΛCDM. Therefore, explanations to this issue are mandatory to unveil its secrets. Despite its success, ΛCDM is unable to give a satisfying explanation to the tension problem. Unless some systematic errors might be hidden in the observable measurements, physics beyond the standard model of cosmology must be advocated. In this perspective, we study a phantom dynamical dark energy model as an alternative to ΛCDM in order to explain the aforementioned issues. This phantom model is characterised by one extra parameter, Ω pdde , compared to ΛCDM. We obtain a strong positive correlation between H0 and Ω pdde , for all data combinations. Using Planck measurements together with BAO and Pantheon, we find that the H0 and the S8 tensions are 3σ and 2.6σ, respectively. By introducing a prior on the absolute magnitude, MB, of the SN Ia, the H0 tension decreases to 2.27σ with H0 = 69.76 +0.75 −0.82 km s −1 Mpc −1 and the S8 tension reaches the value 2.37σ with S8 = 0.8269 +0.011 −0.012 .

International audienceShared memory is a critical issue for large distributed systems. Despite several data consistency protocols have been proposed, the selection of the protocol that best suits to the application requirements and system constraints remains a challenge. The development of multi-consistency systems, where different protocols can be deployed during runtime, appears to be an interesting alternative. In order to explore the design space of the consistency protocols a fast and accurate method should be used. In this work we rely on a compilation toolchain that transparently handles data consistency decisions for a multi-protocol platform. We focus on the analytical evaluation of the consistency configuration that stands within the optimization loop. We propose to use a TLM NoC simulator to get feedback on expected network contentions. We evaluate the approach using five workloads and three different data consistency protocols. As a result, we are able to obtain a fast and accurate evaluation of the different consistency alternatives