PPT-Accelerating Precise Race Detection Using Commercially-Available Hardware Transactional
Author : coveurit | Published Date : 2020-08-06
Serdar Tasiran Koc University Istanbul Turkey Microsoft Research Redmond Hassan Salehe Matar Ismail Kuru Koc University Istanbul Turkey Roman Dementiev
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Accelerating Precise Race Detection Using Commercially-Available Hardware Transactional: Transcript
Serdar Tasiran Koc University Istanbul Turkey Microsoft Research Redmond Hassan Salehe Matar Ismail Kuru Koc University Istanbul Turkey Roman Dementiev Intel Munich Germany. Avg Access Time 2 Tokens Number of Controllers Average Access Time clock cyles brPage 16br Number of Tokens vs Avg Access Time 9 Controllers Number of Tokens Average Access Time clock cycles brPage 17br brPage 18br tumde Abstract So far transactional memoryalthough a promising techniquesuffered from the absence of an ef64257cient hardware implementation The upcoming Haswell microarchitecture from Intel introduces hardware transactional memory HTM in mainstream Thermally processed commercially sterile products are addressed in two subparts of the current regulations The two sections are identical except that Subpart G 318300 311 pertains to meat products and Subpart X 381300 to 311 pertains to poultry pro Hardware: Challenges and Opportunities. Author. : Bingsheng He. (Nanyang Technological University, Singapore) . Speaker. : . Jiong . He . (Nanyang Technological University, Singapore. ). 1. What is Approximate Hardware?. LPAR 2008 . –. Doha, Qatar. Nikolaj . Bjørner. , . Leonardo de Moura. Microsoft Research. Bruno . Dutertre. SRI International. Satisfiability Modulo Theories (SMT). Accelerating lemma learning using joins. Invariants. Arie Gurfinkel (SEI / CMU). Anton . Belov. (UCD / Synopsys). Joao Marques-. Silva (UCD). Copyright 2013 Carnegie Mellon . University. This . material is based upon work funded and supported by the Department of Defense under Contract No. FA8721-05-C-0003 with Carnegie Mellon University for the operation of the Software Engineering Institute, a federally funded research and development center. Rajwar. , R., . Herlihy. , M., and Lai, K. 2005. presented by . VasilyVolkov. , 04/30/08. Motivation. Transactional Memory is good. Never deadlocks. Makes concurrent programming easier. But requires programmer to be aware of. . G. Riddone. 25.06.2010. CLIC meeting . Contribution from R. Nousiainen, J. Huopana, T. Charles. Content . Recall of main issues. Recall of module heat dissipation . Module cooling scheme. Thermo-mechanical analysis: . Swarnendu Biswas. , UT Austin. Man Cao. , Ohio State University. Minjia Zhang. , Microsoft Research. Michael D. Bond. , Ohio State University. Benjamin P. Wood. , Wellesley College. CC 2017. A Java Program With a Data Race. John Erickson, . Madanlal. . Musuvathi. , Sebastian Burckhardt, Kirk . Olynyk. Microsoft . Research. Motivations. Need for race detection in Kernel modules. Also must detect race conditions between hardware and Kernel. Zajac. , Edward J. & Olsen, Cyrus P.. Journal of Management Studies. , 30 (1): 131-145. Presented by Nan Zhang. Overview. Motivation. Two limiting emphases of transaction cost analysis. A transactional value framework. Applications, Availability, and Marketability. Benjamin . Babineau. Matthew Best. Sean Farrell . Outline. Why This Project?. Background. Types of Biosensors. Applications. Commercially Available Biosensors. Spiegelman. *. , Guy . Golan-. Gueta. †. , and Idit Keidar. †*. *. Technion. . †. Yahoo Research. 1. Agenda. Motivation. Concurrent Data Structure Libraries (CDSLs) vs Transactional Memory. Introducing: Transactional Data Structure Libraries (TDSL). The Mistakes We Make. “Leadership can be developed. However, it cannot be ‘promoted.’”. -Dan Chase (June 16. th,. 2015). “There go the people. I must follow them, for I am their leader." .
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