T
Tatiana Shpeisman
Researcher at Intel
Publications - 86
Citations - 3152
Tatiana Shpeisman is an academic researcher from Intel. The author has contributed to research in topics: Transactional memory & Compiler. The author has an hindex of 31, co-authored 84 publications receiving 2998 citations. Previous affiliations of Tatiana Shpeisman include University of Maryland, College Park & PARC.
Papers
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Journal ArticleDOI
Compiler and runtime support for efficient software transactional memory
Ali-Reza Adl-Tabatabai,Brian T. Lewis,Vijay Menon,Brian R. Murphy,Bratin Saha,Tatiana Shpeisman +5 more
TL;DR: A high-performance software transactional memory system (STM) integrated into a managed runtime environment is presented and the JIT compiler is the first to optimize the overheads of STM, and novel techniques for enabling JIT optimizations on STM operations are shown.
Proceedings ArticleDOI
Open nesting in software transactional memory
Yang Ni,Vijay Menon,Ali-Reza Adl-Tabatabai,Antony L. Hosking,Richard L. Hudson,J. Eliot B. Moss,Bratin Saha,Tatiana Shpeisman +7 more
TL;DR: New language constructs to support open nesting in Java are described, and it is demonstrated how these constructs can be mapped efficiently to existing STM data structures, demonstrating how open nesting can enhance application scalability.
Proceedings ArticleDOI
Enforcing isolation and ordering in STM
Tatiana Shpeisman,Vijay Menon,Ali-Reza Adl-Tabatabai,Steven Balensiefer,Dan Grossman,Richard L. Hudson,Katherine F. Moore,Bratin Saha +7 more
TL;DR: The results on a set of Java programs show that strong atomicity can be implemented efficiently in a high-performance STM system and introduces a dynamic escape analysis that differentiates private and public data at runtime to make barriers cheaper and a static not-accessed-in-transaction analysis that removes many barriers completely.
Posted Content
MLIR: A Compiler Infrastructure for the End of Moore's Law.
Chris Lattner,Jacques A. Pienaar,Mehdi Amini,Uday Bondhugula,River Riddle,Albert Cohen,Tatiana Shpeisman,Andrew Davis,Nicolas Vasilache,Oleksandr Zinenko +9 more
TL;DR: Evaluation of MLIR as a generalized infrastructure that reduces the cost of building compilers-describing diverse use-cases to show research and educational opportunities for future programming languages, compilers, execution environments, and computer architecture.