Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Caroline Trippel"'
Publikováno v:
Proceedings of the 49th Annual International Symposium on Computer Architecture.
We propose RecShard, a fine-grained embedding table (EMB) partitioning and placement technique for deep learning recommendation models (DLRMs). RecShard is designed based on two key observations. First, not all EMBs are equal, nor all rows within an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c5c8644d0306056a54cedb7b2b91f96
http://arxiv.org/abs/2201.10095
http://arxiv.org/abs/2201.10095
Publikováno v:
MICRO
Modern hardware complexity makes it challenging to determine if a given microarchitecture adheres to a particular memory consistency model (MCM). This observation inspired the Check tools, which formally check that a specific microarchitecture correc
Autor:
Jose Rodrigo Sanchez Vicarte, Christopher W. Fletcher, David Kohlbrenner, Pradyumna Shome, Caroline Trippel, Nandeeka Nayak, Adam Morrison
Publikováno v:
ISCA
Microarchitectural attacks have plunged Computer Architecture into a security crisis. Yet, as the slowing of Moore's law justifies the use of ever more exotic microarchitecture, it is likely we have only seen the tip of the iceberg. To better anticip
Publikováno v:
IEEE Micro. 39:84-93
Many hardware security exploits result from the combination of well-known attack classes with newly exploited hardware features. CheckMate is an approach and automated tool for evaluating microarchitectural susceptibility to specified attack classes,
Autor:
Meghan Cowan, Caroline Trippel, Brandon Reagen, Deeksha Dangwal, Vincent T. Lee, Armin Alaghi
Publikováno v:
HASP@MICRO
Users are demanding increased data security. As a result, security is rapidly becoming a first-order design constraint in next generation computing systems. Researchers and practitioners are exploring various security technologies to meet user demand
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9cba14c6e27967812dc628422b666179
http://arxiv.org/abs/2105.00378
http://arxiv.org/abs/2105.00378
Autor:
David Brooks, Samuel Hsia, Udit Gupta, Carole-Jean Wu, Gu-Yeon Wei, Mark Wilkening, Caroline Trippel
Publikováno v:
ASPLOS
Neural personalized recommendation models are used across a wide variety of datacenter applications including search, social media, and entertainment. State-of-the-art models comprise large embedding tables that have billions of parameters requiring
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ac566a362cf42bcfbb7584060bf2d39
http://arxiv.org/abs/2102.00075
http://arxiv.org/abs/2102.00075
Autor:
Deeksha Dangwal, Vincent T. Lee, Brandon Reagen, Caroline Trippel, Meghan Cowan, Armin Alaghi
Publikováno v:
PLDI
Homomorphic encryption (HE) is a privacy-preserving technique that enables computation directly on encrypted data. Despite its promise, HE has seen limited use due to performance overheads and compilation challenges. Recent work has made significant
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ba3500bfbb7c1bb9d65ad0f85bf12d7
http://arxiv.org/abs/2101.07841
http://arxiv.org/abs/2101.07841
Publikováno v:
ISCA
Memory consistency models (MCMs) specify the legal ordering and visibility of shared memory accesses in a parallel program. Traditionally, instruction set architecture (ISA) MCMs assume that relevant program-visible memory ordering behaviors only res
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f2e2e2a5148fba365a0e3eb7d929d07
Publikováno v:
IEEE Micro. 38:58-68
Memory consistency models (MCMs) govern inter-module interactions in a shared memory system and are defined at the various layers of the hardware-software stack. TriCheck is the first tool for full-stack MCM verification. Using TriCheck, we uncovered