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INSTRUCTION LEVEL PARALLELISM PDF

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Instruction Level Parallelism (ILP). • Basic idea: Execute several instructions in parallel. • We already do pipelining – But it can only push thtough at most 1 inst /. Instruction-level Parallelism. Report for Software View of Processor Architectures. COMP Godfrey van der Linden. 1. Introduction. Instruction-Level Parallelism (ILP). Fine-grained parallelism. Obtained by: • instruction overlap in a pipeline. • executing instructions in parallel (later, with.


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PDF | The instruction level parallelism (ILP) is not a new idea. It has been in practice since and became a much more significant force in computer design. Instruction Level Parallelism and Superscalar. Processors. Computer Organization and Architecture. What does Superscalar mean? • Common instructions. Today's Goals. • What is instruction-level parallelism? • What do processors do to extract ILP? • Not “how do they do that” (future lecture).

For instance, having stable from one data set to another, and frequent too many conditionals within a loop may either pre- branches are biased—often either repeatedly taken or clude the use of software pipelining or yield inefficient repeatedly not taken.

Instruction Level Parallelism

This allows a branch to be stat- code. In addition, software pipelines traditionally ically predicted as either taken or not taken. When pro- complete iterations at a rate independent of the path file statistics are unavailable or branches are balanced taken through the loop, which unduly penalizes short taken at about the same frequency as not taken , inac- paths.

Advanced software pipelining techniques may curate static branch prediction can lead to premature alleviate these deficiencies. Branch profiles are gathered using sample input Architectural support data to execute instrumented program runs.

We can The evaluation of real-application performance is eliminate this unpopular step by using compile time far more difficult than evaluating segments or kernels, analysis to predict branch profiles. Compile time pre- for which handcoding machine instructions might suf- diction alone can be improved but may never match fice. That is why compilers are the only way to evalu- the accuracy of sample runs. An alternate solution might be to develop larger and Novel architectures.

To assess new architectures, more general types of regions.

It is possible to gener- compilers must incorporate proposed architectural alize the linear control flow required by traces and features. Speculation, for example, has long been used superblocks to support scheduling of nonlinear pro- to enhance ILP performance by allowing compile time gram regions.

Global schedulers, for instance, move movement of code across basic-block boundaries. Exception pro- more performance when confronted with difficult-to- cessing and debugging often reveal the effects of code predict control flow. However, global schedulers must transformations that should have transparently accel- carefully balance execution performance and compi- erated code.

Processing an exception or returning lation speed. Algorithmic efficiency is critical when control to the debugger exposes results inconsistent schedulers process large amounts of code with arbi- with the sequential view of the program. Global schedulers are also at To alleviate this problem, new ILP architectures risk of speculatively executing too many operations provide hardware support for speculative execu- from paths that are, in fact, never executed.

The heuristics based on approximations needed to achieve hardware allows the speculative movement of code at acceptable compilation speed. Because these approx- compile time while presenting the illusion of sequen- imations simplify complex problems, they sometimes tial program execution.

Compilers may need to gen- yield inefficient results. For instance, schedulers may erate complex recovery code to preserve this illusion. Scheduling and register allo- architectures to enhance performance of difficult-to- cation interact in a complex manner that can intro- predict branches.

Code size can also accelerate code containing sequences of dependent be exaggerated when code is prepared for scheduling branches. The scheduler may also directly add too research is far from complete. We need techniques highly concurrent register access, yet it is difficult to to better balance these complex trade-offs. A variety of ister file. So some processor architectures may incor- challenges.

Multimedia enhancements provide more parallel register access with simpler operations support SIMD-like parallelism by packing to existing hardware. This requires additional compiler capabil- multiple narrow operands into a single, wide data languages ities to distribute operands across multiple register word. This wide word performs up to eight narrow files. Although the Multiflow processor and compiler operations at once.

If general-purpose programs are and use distributed register files for a limited class of appli- to use these extensions, we must develop new compiler application cations,3 further research is needed to facilitate the technology that exploits multimedia operations when development broad use of distributed register files. Memory refer- improving performance. This often results in long systems.

These effects are very vide a software architecture that partitions applica- costly in applications that manipulate large data sets. It also must Innovation in both compilers and memory architec- incorporate a variety of analyses and optimization tures could alleviate these effects. Careful appli- Memory load operations may have either short cation partitioning and better algorithms for analysis latencies to access small data sets those that fit into the and optimization of regions can speed compilation.

For static scheduling, a com- Language evolution piler needs to differentiate these loads. Prefetch is one Even when applications have sufficient parallelism, technique to assist an ILP processor in overlapping the compiler is often unable to exploit it because of long-latency memory references that miss in the cache.

For example, the introduction of vector and els.

A variety of ILP-friendly enhancements to existing Data speculation uses additional hardware to languages and application development methodolo- improve the amount of ILP in the presence of poten- gies could improve the performance of future systems. Its acceptance in measuring performance with uses of its result to move upward across a previous SPEC benchmarks indicates a growing industry accep- store, which improves the operation schedule.

The load tance of ILP. Another enhancement, compiler direc- operation may now yield an incorrect result because tives, can substantially enhance ILP performance for of its adjusted position in the schedule. Hardware languages like C. In the future, applications may be detects when an alias occurs, and a correct result is cal- tuned for ILP execution using directives much like culated after completion of any stores that might alias. Existing architectures. Such pro- niques.

For example, a compiler can schedule an oper- tocols can erect huge barriers to ILP performance, ation speculatively on an existing architecture if it can almost requiring the sequential execution of all oper- preclude the introduction of an exception.

We can ations. Hopefully, the desire for additional perfor- adapt several ILP techniques to provide utility on mance will stimulate system developers to adopt existing processor architectures.

The introduction of multimedia operations into gen- Almost all ILP research has studied performance for eral-purpose architectures creates important compiler Fortran and C. Such research has yet to consider newer 68 Computer..

ILP as well as quantify relationships between languages 9. Kathail, M. Schlansker, and B. Rau, HPL Play- and delivered performance. To be of practical value, Doh Architecture Specification: Version 1. Alto, Calif. Silberman and K. Mahlke et al. To advance, ILP compilers will require an enormous Gallagher et al. Multimedia enhancements provide more parallel register access with simpler operations support SIMD-like parallelism by packing to existing hardware.

This requires additional compiler capabil- multiple narrow operands into a single, wide data languages ities to distribute operands across multiple register word. This wide word performs up to eight narrow files. Although the Multiflow processor and compiler operations at once.

If general-purpose programs are and use distributed register files for a limited class of appli- to use these extensions, we must develop new compiler application cations,3 further research is needed to facilitate the technology that exploits multimedia operations when development broad use of distributed register files. Memory refer- improving performance. This often results in long systems.

These effects are very vide a software architecture that partitions applica- costly in applications that manipulate large data sets. It also must Innovation in both compilers and memory architec- incorporate a variety of analyses and optimization tures could alleviate these effects. Careful appli- Memory load operations may have either short cation partitioning and better algorithms for analysis latencies to access small data sets those that fit into the and optimization of regions can speed compilation.

For static scheduling, a com- Language evolution piler needs to differentiate these loads.

Prefetch is one Even when applications have sufficient parallelism, technique to assist an ILP processor in overlapping the compiler is often unable to exploit it because of long-latency memory references that miss in the cache. For example, the introduction of vector and els. A variety of ILP-friendly enhancements to existing Data speculation uses additional hardware to languages and application development methodolo- improve the amount of ILP in the presence of poten- gies could improve the performance of future systems.

Its acceptance in measuring performance with uses of its result to move upward across a previous SPEC benchmarks indicates a growing industry accep- store, which improves the operation schedule. The load tance of ILP.

Instruction Level Parallelism

Another enhancement, compiler direc- operation may now yield an incorrect result because tives, can substantially enhance ILP performance for of its adjusted position in the schedule. Hardware languages like C. In the future, applications may be detects when an alias occurs, and a correct result is cal- tuned for ILP execution using directives much like culated after completion of any stores that might alias.

Existing architectures. Such pro- niques. For example, a compiler can schedule an oper- tocols can erect huge barriers to ILP performance, ation speculatively on an existing architecture if it can almost requiring the sequential execution of all oper- preclude the introduction of an exception. We can ations. Hopefully, the desire for additional perfor- adapt several ILP techniques to provide utility on mance will stimulate system developers to adopt existing processor architectures.

The introduction of multimedia operations into gen- Almost all ILP research has studied performance for eral-purpose architectures creates important compiler Fortran and C. Such research has yet to consider newer 68 Computer.. ILP as well as quantify relationships between languages 9. Kathail, M. Schlansker, and B. Rau, HPL Play- and delivered performance. To be of practical value, Doh Architecture Specification: Version 1.

Alto, Calif. Silberman and K. Mahlke et al. To advance, ILP compilers will require an enormous Gallagher et al. Hank, W. Hwu, and B. Parallel Programming, Vol. Although costly to develop, a number of ILP compilers exist both in academia and in industry, and we are just entering an era when Michael Schlansker is a department scientist at processors supporting ILP are generally available. His research interests include computer architecture, compilers, and embed- ded systems design.

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He is a mem- 1. Lee, A. Kwok, and F. Architectural Support for Pro- Thomas M. Jim Dehnert is a principal engineer in compiler devel- 2. Ruttenberg et al. His research interests Optimal vs.

Programming Language Design and Imple- pipelining, register allocation, and optimization. Dehnert has a PhD in applied mathematics from the 3. Kemal Ebcioglu is manager of the High Performance 4. Dehnert and R.

Ebcioglu received a PhD in computer science 5. Hwu et al. Supercomput- ing, Vol. Jesse Z. Schlansker and V. Micro- Carol L. Her interests include computer architecture as well as 7. Fisher and S. Archi- lelism. She received her masters degree in computer tectural Support for Programming Languages and Operat- science from the University of California at Berkeley. Moon and K. CA ; schlansk hplmss.

December 69 Related Papers. Banerjee has served as a research staff member at Honeywell, Fairchild, Control Data and Intel corporations. He has published a number of papers and books on restructuring compilers, including encyclopedia articles and a series of books on loop transformations. He co-founded MZ Research and currently manages a team of research scientists. He is leading the research and development of novel algorithms for fraud detection, anomaly detection in security and operational data.

Prior to joining Machine Zone, he was a lead in the Data Fidelity Team at Twitter and open sourced standalone R packages for anomaly detection and breakout detection. He received Ph. He authored over peer-reviewed papers and several books. JavaScript is currently disabled, this site works much better if you enable JavaScript in your browser.

Computer Science Communication Networks. Free Preview. Presents an unprecedented text, uniquely dedicated to Instruction Level Parallelism ILP Provides a detailed examination of ILP architectures Offers practical descriptions of key scheduling algorithms for extracting ILP at compile time Illustrates how algorithms can be applied to streaming computations and compilation for Graphics Processing Units GPUs Equips readers with a resourceful and comprehensive bibliography that spans over five decades see more benefits.This book precisely formulates and simplifies the presentation of Instruction Level Parallelism ILP compilation techniques.

Rau, HPL Play- and delivered performance. Analysis techniques that delivered sat- stood, and exciting opportunities exist for partial isfactory results on earlier sequential processors may inlining and interprocedural optimization. Compilers may need to gen- yield inefficient results. He co-founded MZ Research and currently manages a team of research scientists. However, typical programs pro- tional operations.

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