PPT-On Quantification of Accuracy Loss in Approximate Computing

Author : faustina-dinatale | Published Date : 2018-03-21

Ulya R Karpuzcu ukarpuzcumnedu 12012015 Outline Background Pitfalls amp Fallacies Practical Guidelines 2 12012015 On Quantification of Accuracy Loss in Approximate

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On Quantification of Accuracy Loss in Approximate Computing: Transcript

Ulya R Karpuzcu ukarpuzcumnedu 12012015 Outline Background Pitfalls amp Fallacies Practical Guidelines 2 12012015 On Quantification of Accuracy Loss in Approximate Computing. University of Washington. Adrian Sampson, . Hadi. Esmaelizadeh,. 1. Michael . Ringenburg. , . Reneé. St. Amant,. 2. . Luis . Ceze. , . Dan Grossman. , Mark . Oskin. , Karin Strauss,. 3. and Doug Burger. Michael . Carbin. with . Sasa. . Misailovic. , Hank Hoffmann. , . Deokhwan. . Kim, . Stelios. . Sidiroglou. , Martin . Rinard. MIT. Challenges for Programming. Expression (specifying approximations). Hardware: Challenges and Opportunities. Author. : Bingsheng He. (Nanyang Technological University, Singapore) . Speaker. : . Jiong . He . (Nanyang Technological University, Singapore. ). 1. What is Approximate Hardware?. Michael Carbin. Deokhwan. Kim, . Sasa. . Misailovic. , and Martin C. . Rinard. Approximate Computing. Media Processing, Machine Learning, Search. Solution Space: Accuracy versus Cost. Accuracy. Time/. Daya . S . Khudia. , . Babak. . Zamirai. , . Mehrzad. . Samadi. and Scott . Mahlke. June 17, 2015. Computer Engineering Laboratory. University of . Michigan. . . . Approximate Computing. . COMPUTATIONAL. . NANOELECTRONICS. W7. : . Approximate. Computing. & . Bayesian. Networks. , . 31. /1. 0. /201. 6. FALL 201. 6. Mustafa. . Altun. Electronics & Communication Engineering. Andrew B. Kahng, . Seokhyeong Kang . VLSI CAD LABORATORY, . UC. San Diego. 49. th. Design Automation Conference. June 6. th. , 2012. Outline. Background and Motivation. Accuracy Configurable Adder Design. Abbas Rahimi, . Andrea . Marongiu. ,. . Rajesh K. Gupta, Luca . Benini. UC San Diego, and . University of Bologna . Micrel.deis.unibo.it. /. MultiTherman. variability.org. Outline. Introduction. and . Sasa . Misailovic. MIT CSAIL. Collaborators. Martin . Rinard. , Michael . Carbin. , . Stelios. . Sidiroglou. , Henry Hoffmann, . Deokhwan. Kim, Fan Long, Daniel Roy, . Zeyuan. Allen Zhu, Michael Kling, . Milos Gligoric. 1. , Sarfraz Khurshid. 1. , Sasa Misailovic. 2. , . August Shi. 2. ICSE NIER 2017. Buenos Aires, . Argentina. May 24, 2017. 1. CCF-1409423, CCF-1421503,. CCF-1566363, CCF-1629431,. CCF-1319688, CNS-1239498. University of Washington. Adrian Sampson, . Hadi. Esmaelizadeh,. 1. Michael . Ringenburg. , . Reneé. St. Amant,. 2. . Luis . Ceze. , . Dan Grossman. , Mark . Oskin. , Karin Strauss,. 3. and Doug Burger. Milos Gligoric. 1. , Sarfraz Khurshid. 1. , Sasa Misailovic. 2. , . August Shi. 2. ICSE NIER 2017. Buenos Aires, . Argentina. May 24, 2017. 1. CCF-1409423, CCF-1421503,. CCF-1566363, CCF-1629431,. CCF-1319688, CNS-1239498. Michael Carbin. Deokhwan. Kim, . Sasa. . Misailovic. , and Martin C. . Rinard. Approximate Computing. Media Processing, Machine Learning, Search. Solution Space: Accuracy versus Cost. Accuracy. Time/. Vaginal Delivery. A Step by Step Guide. WHY DO WE CARE ABOUT QBL?. Current. recommendations:. 1) After . delivery of baby, provider and primary RN agree on amniotic fluid level in calibrated drape and .

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