PDF-Coterminous locality and coterminous group data prefetching on chip multiprocessors

CMP 2 or 4 cores 32GHz ROB size 128 FetchExecRetireCommit width 4 7 5 3 Branch predictor Gshare 64KB 4K BTB Branch misprediction penalty 10 cycles Processor side prefetcher Stride. 142 brPage 2br Taxonomy SISD single instruction and sing le data stream uniprocessor MISD no commercial multiprocessor imagine data going through a pipeline of execution engines SIMD vector architectures lower flexibility MIMD most multiprocessors to Optimization. Techniques. . Presented by . Preethi Rajaram. CSS 548 Introduction to Compilers . Professor Carol Zander. Fall 2012 . Why?. Processor Speed . -. increasing at a faster rate than the memory speed. ExaScale. . Challenges and Potential Solutions. Bill Dally. Chief Scientist, . NVIDIA. Bell Professor of Engineering, Stanford University. Two Key Challenges. Programmability. Writing an efficient parallel program is hard. Tomofumi Yuki . . INRIA . Rennes. Antoine . Morvan. . . ENS . Cachan. Bretagne. Steven . Derrien. . University of Rennes 1. Memory Optimizations. Memory Wall. Zhenhua . Guo. , Geoffrey Fox, Mo Zhou. Outline. Introduction. Data Locality and Fairness. Experiments. Conclusions. MapReduce Execution Overview. 3. Google File System. Read input data. Data locality. Zhenhua . Guo. , Geoffrey Fox, Mo Zhou. Outline. Introduction. Analysis of Data Locality. Optimality of Data Locality. Experiments. Conclusions. MapReduce Execution Overview. 3. Google File System. Read input data. Seth Pugsley. Predicting the Future. Where have we seen prediction before?. Does it always work?. Prefetching is prediction. Predict which cache line will be used next, and place it in the cache before it is used. Zhenhua . Guo. , Geoffrey Fox, Mo Zhou. Outline. Introduction. Analysis of Data Locality. Optimality of Data Locality. Experiments. Conclusions. MapReduce Execution Overview. 3. Google File System. Read input data. . Smruti. R. . Sarangi. Contents. Motivation for Prefetching. Simple Schemes. Recent Work. Proactive Instruction Fetching. Return Address Stack Directed Prefetching. Pentium 4 Trace Cache. Exploiting Unique Opportunities. Ahmad . Lashgar. and . Amirali. . Baniasadi. ECE Department. University of Victoria. 1. Overview. Prefetching Challenges:. Prefetching accuracy. Timeliness. Bandwidth control. Tomofumi Yuki . . INRIA . Rennes. Antoine . Morvan. . . ENS . Cachan. Bretagne. Steven . Derrien. . University of Rennes 1. Memory Optimizations. Memory Wall. Madhu. . Sudan. Harvard. April 9, 2016. Skoltech: Locality in Coding Theory. 1. Error-Correcting Codes. (Linear) Code . .. : Finite field with . elements.. . block length. . message length. : Rate of . Results and Awards. Seth . Pugsley. Thanks!. Big thanks to Hyesoon Kim and the Program Committee. Babak. . Falsafi. Mike . Ferdman. . Aamer. Jaleel. Daniel Jiménez Calvin Lin . Moin. Qureshi. Daniel Burk. What is a Predictive Model?. A GIS based model attempting to determine fossil locality potential. 1. Start with known fossil localities. 2. Compare their characteristics to other places.