PPT-SIMD Lane Decoupling Improved Timing-Error Resilience

Evgeni Krimer UT Austin Patrick Chiang Oregon State Mattan Erez UT Austin All systems powerenergy bound The good Transistor still following Moores Law The bad Transistor power efficiency improving too slowly. A welldesigned decoupling plan helps keep utility pro57375ts steady and customers energy costs in checkand it removes the disincentive for utilities to promote energy ef57375ciency programs 1 These are costs that are relatively 57375xed in the short Decoupling error detection and error correction. Error detection can be done cheaply while correction is expensive. Hence, decoupling detection and correction is beneficial if errors are rare events, SIMD architectures. A data parallel architecture. Applying the same instruction to many data. Save control logic. A related architecture is the vector architecture. SIMD and vector architectures offer high performance for . Tailoring . SIMD Execution using . Heterogeneous Hardware . and Dynamic Configurability. Yongjun Park. 1. , Jason Jong Kyu Park. 1. , Hyunchul Park. 2. ,. and Scott Mahlke. 1. December. 3, 2012. 1. a tutorial. Daniel Lidar. QEC11. For a great DD tutorial . see . Lorenza. Viola’s talk in . http. ://qserver.usc.edu/qec07/program.html. S. lides & movie.. This tutorial:. Essential intro material. Tailoring . SIMD Execution using . Heterogeneous Hardware . and Dynamic Configurability. Yongjun Park. 1. , Jason Jong Kyu Park. 1. , Hyunchul Park. 2. ,. and Scott Mahlke. 1. December. 3, 2012. 1. Farzad Khorasani. , . Rajiv Gupta. , . Laxmi. N. . Bhuyan. University of California Riverside. Scalable SIMD-Efficient Graph Processing on GPUs. Graph Processing. Building blocks of data analytics.. For Evaluating Error Resilience of GPGPU Applications. Bo . Fang . , . Karthik. . Pattabiraman. , . Matei. . Ripeanu. ,. The . University of British . Columbia. Sudhanva. . Gurumurthi. . AMD Research. with . random diagonal-. unitaries. Yoshifumi Nakata. Universitat. . Autonoma. de Barcelona & The University of Tokyo . arXiv:1502.07514 & arXiv:1509.05155. Joint work with . C. . Hirche. , C. Morgan, and A. Winter. Farzad Khorasani. , . Rajiv Gupta. , . Laxmi. N. . Bhuyan. University of California Riverside. Scalable SIMD-Efficient Graph Processing on GPUs. Graph Processing. Building blocks of data analytics.. Andrew B. . Kahng. , . Seokhyeong. Kang . and . Jiajia Li. UC . San . Diego VLSI CAD Laboratory. Outline. Background and Motivation. Problem Statement. Related Work. Our Methodology. Experimental Setup and Results. May 20, 2014. Tiffany Idziak, LMSW, CTS. Bob VandePol, LMSW. The Calling to Compassion. There is no greater honor….there is no greater responsibility...than to be there for someone on the worst day of their life. Jeffrey Kissel. LIGO Hanford Controls Engineer. LIGO Calibration Group Co-Chair. G1800393-v2. 1. Inspiration. G1800393-v2. 2. PRL. . 116.23 (2016): . 231102. 2G , 3G, Space, and PTAs. will have events with SNRs of O(~100). on. . the. . Tegra. Xavier. Kristoffer Robin Stokke, . PhD. Huddly. Why. . Learn. to . Optimize. . with. Assembler?. Historically. : . Constrained. hardware. Entire. . applications. . written.