'Data dependences' diaporamas de présentation

Advanced Computer Architecture 5MD00 / 5Z033 ILP architectures with emphasis on Superscalar

Advanced Computer Architecture 5MD00 / 5Z033 ILP architectures with emphasis on Superscalar. Henk Corporaal www.ics.ele.tue.nl/~heco/courses/ACA h.corporaal@tue.nl TUEindhoven 2013. Topics. Introduction Hazards Out-Of-Order (OoO) execution: Dependences limit ILP: dynamic scheduling

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Computer Architecture

Computer Architecture. Goal: Build the best possible “processor” Here’s a piece of silicon Here some of its properties Tell me what to build 1. Understand your building blocks 2. Understand what is “best” means 3. Take into account design/production time. Track Record. Evolution?.

1.03k views • 90 slides

Advanced Computer Architecture 5MD00 / 5Z033 ILP architectures with emphasis on Superscalar

Advanced Computer Architecture 5MD00 / 5Z033 ILP architectures with emphasis on Superscalar. Henk Corporaal www.ics.ele.tue.nl/~heco/courses/ACA h.corporaal@tue.nl TUEindhoven 2013. Topics. Introduction Hazards Out-Of-Order (OoO) execution: Dependences limit ILP: dynamic scheduling

964 views • 82 slides

Advanced Computer Architecture 5MD00 / 5Z033 ILP architectures with emphasis on Superscalar

Advanced Computer Architecture 5MD00 / 5Z033 ILP architectures with emphasis on Superscalar. Henk Corporaal www.ics.ele.tue.nl/~heco/courses/ACA h.corporaal@tue.nl TUEindhoven 2013. Topics. Introduction Hazards Out-Of-Order (OoO) execution: Dependences limit ILP: dynamic scheduling

956 views • 82 slides

Compiler Optimization of scalar and memory resident values between speculative threads.

Compiler Optimization of scalar and memory resident values between speculative threads. Antonia Zhai et. al. P. P. P. P. C. C. C. C. C. Improving Performance of a Single Application. T1. T2. T3. T4. dependence. Store 0x86. Load 0x86. ?. Chip Boundary.

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Data Dependence Based Testability Transformation in Automated Test Generation

Data Dependence Based Testability Transformation in Automated Test Generation. Presented by: Qi Zhang. Outline. Introduction to test data generation Test data generation methods Data dependence oriented test generation Testability transformation in test data generation Conclusions.

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Advanced Microarchitecture

Advanced Microarchitecture. Lecture 2: Pipelining and Superscalar Review. Pipelined Design. Motivation: Increase throughput with little increase in cost (hardware, power, complexity, etc.) Bandwidth or Throughput = Performance BW = num. tasks/unit time

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Instruction-level Parallelism

Instruction-level Parallelism. Instruction-Level Parallelism (ILP): overlapping of executions among instructions that are mutually independent. Difficulties in exploiting ILP: various hazards that impose dependency among instructions, as a result:

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Scalable Dynamic Analysis for Automated Fault Location and Avoidance

Scalable Dynamic Analysis for Automated Fault Location and Avoidance. Rajiv Gupta. Funded by NSF grants from CPA , CSR , & CRI programs and grants from Microsoft Research. Motivation. Software bugs cost the U.S. economy about $59.5 billion each year [ NIST 02 ] . Embedded Systems

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Administrative

CS4961 Parallel Programming Lecture 8: Dependences and Locality Optimizations Mary Hall September 15, 2011. Administrative. I will be on travel Tuesday, September 20 Nikhil will hold lab hours to complete the programming assignment ROOM L130.

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Introduction to Instruction Scheduling

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Branch Hazards in the Pipelined Processor

Branch Hazards in the Pipelined Processor. Dependences. Data dependence : one instruction is dependent on another instruction to provide its operands. Control dependence (aka branch dependences ): one instructions determines whether another gets executed or not.

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Extended Whole Program Paths

Extended Whole Program Paths. Sriraman Tallam Rajiv Gupta Xiangyu Zhang University of Arizona. Control Flow and Dependence Traces. Control Flow Traces Sequence of basic blocks. Identification of hot paths. Path Sensitive Instruction Scheduling and Optimization.

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Lecture 1: Introduction Instruction Level Parallelism & Processor Architectures

Lecture 1: Introduction Instruction Level Parallelism & Processor Architectures. Instruction Level Parallelism (ILP). Simultaneous execution of multiple instructions. do { Swap = 0; for (I = 0; I<Last; I++) { if (Tab[I] > Tab[I+1]) { Temp = Tab[I];

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Lecture 7 Instruction Scheduling

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Lecture 6: Static ILP

Lecture 6: Static ILP. Topics: loop analysis, SW pipelining, predication, speculation (Section 2.2, Appendix G) Assignment 2 posted; due in a week. Loop Dependences. If a loop only has dependences within an iteration, the loop

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Understanding Parallelism-Inhibiting Dependences in Sequential Java Programs

Understanding Parallelism-Inhibiting Dependences in Sequential Java Programs. Atanas ( Nasko ) Rountev Kevin Van Valkenburgh Dacong Yan P. Sadayappan Ohio State University. Overview and Motivation. Multi-core hardware presents a great software evolution challenge Our goals

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Lecture 12: Advanced Static ILP

Lecture 12: Advanced Static ILP. Topics: parallel loops, software speculation (Sections 4.5-4.10). Predication. A branch within a loop can be problematic to schedule Control dependences are a problem because of the need to re-fetch on a mispredict

229 views • 11 slides