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Représentation dynamique de la liste des copies pour le passage à l'échelle des protocoles de cohérence de cache

Abstract : Cache coherence protocol scalability problem for parallel architecture is also a problem for on chip architecture, following the emergence of manycores architectures. There are two protocol classes : snooping and directory-based.Protocols based on snooping, which send coherence information to all caches, generate a lot of messages whose few are useful.On the other hand, directory-based protocols send messages only to caches which need them. The most obvious implementation uses a full bit vector whose size depends only on the number of cores. This bit vector represents the sharing set. To scale, a coherence protocol must produce a reasonable number of messages and limit hardware ressources used by the coherence and in particular for the sharing set.To evaluate and compare protocols and their sharing set, we first propose a method based on trace injection in a high-level cache model. This method enables a very fast architectural exploration of cache coherence protocols.We also propose a new dynamic sharing set for cache coherence protocols, which is scalable. With 64 cores, 93% of cache blocks are shared by up to 8 cores.Futhermore, knowing that the operating system looks to place communicating tasks close to each other. Our dynamic sharing set takes advantage from these two observations by using a bit vector for a subset of copies and a linked list. The bit vector corresponds to a rectangle which stores the exact sharing set. The position and shape of this rectangle evolve over application's lifetime. Several algorithms for coherent rectangle placement are proposed and evaluated. Finally, we make a comparison with sharing sets from the state of the art.
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Submitted on : Friday, September 21, 2018 - 6:50:06 PM
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  • HAL Id : tel-01879032, version 1




Julie Dumas. Représentation dynamique de la liste des copies pour le passage à l'échelle des protocoles de cohérence de cache. Architectures Matérielles [cs.AR]. Université Grenoble Alpes, 2017. Français. ⟨NNT : 2017GREAM093⟩. ⟨tel-01879032⟩



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