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International Conference for High Performance Computing, Networking, Storage and Analysis (SC)

作者： Guan, Hui Shen, Xipeng Krim, Hamid North Carolina State Univ Raleigh NC 27695 USA

ISBN: (数字)9781450351140

ISBN: (纸本)9781450351140

Achieving high performance on modern systems is challenging. Even with a detailed profile from a performance tool, writing or refactoring a program to remove its performance issues is still a daunting task for application programmers: it demands lots of program optimization expertise that is often system specific. Vendors often provide some detailed optimization guides to assist programmers in the process. However, these guides are frequently hundreds of pages long, making it difficult for application programmers to master and memorize all the rules and guidelines and properly apply them to a specific problem instance. In this work, we develop a framework named Egeria to alleviate the difficulty. Through Egeria, one can easily construct an advising tool for a certain high performance computing (HPC) domain (e.g., GPU programming) by providing Egeria with a optimization guide or other related documents for the target domain. An advising tool produced by Egeria provides a concise list of essential rules automatically extracted from the documents. At the same time, the advising tool serves as a question-answer agent that can interactively offers suggestions for specific optimization questions. Egeria is made possible through a distinctive multi-layered design that leverages natural language processing techniques and extends them with knowledge of HPC domains and how to extract information relevant to code optimization Experiments on CUDA, OpenCL, and Xeon Phi programming guides demonstrate, both qualitatively and quantitatively, the usefulness of Egeria for HPC.

关键词： program optimization high performance computing natural language processing

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Modeling Cache Coherence Misses on Multicores

Modeling Cache Coherence Misses on Multicores

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IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)

作者： Pan, Xiaoyue Jonsson, Bengt Uppsala Univ Dept Informat Technol S-75105 Uppsala Sweden

ISBN: (纸本)9781479936069

While maintaining the coherency of private caches, invalidation-based cache coherence protocols introduce cache coherence misses. We address the problem of predicting the number of cache coherence misses in the private cache of a parallel application when running on a multicore system with an invalidation-based cache coherence protocol. We propose three new performance models (uniform, phased and symmetric) for estimating the number of coherence misses from information about inter-core data sharing patterns and the individual core's data reuse patterns. The inputs to the uniform and phased models are the write frequency and reuse distance distribution of shared data from different cores. This input can be obtained either from profiling the target application on a single core or by analyzing the data access pattern statically, and does not need a detailed simulation of the pattern of interleaving accesses to shared data. The output of the models is an estimated number of coherence misses of the target application. The output can be combined with the number of other kinds of misses to estimate the total number of misses in each core's private cache. This output can also be used to guide program optimization to improve cache performance. We evaluate our models with a set of benchmarks from the PARSEC benchmark suite on real hardware.

关键词： Cache Coherence program optimization BENCHMARKS Cache memory core Core samples

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Accuracy-Aware optimization of Approximate programs

Accuracy-Aware Optimization of Approximate Programs

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International Conference on Compilers, Architecture and Synthesis for Embedded Systems (CASES)

作者： Misailovic, Sasa MIT CSAIL Cambridge MA 02139 USA

ISBN: (纸本)9781467383202

Many modern applications (such as multimedia processing, machine learning, and big-data analytics) exhibit an inherent tradeoff between performance and the accuracy of the produced results. These applications allow us to investigate new, more aggressive program optimizations. We present a novel approximate optimization framework based on accuracy-aware program transformations. These transformations reduce accuracy of computation in return for improved performance, energy efficiency, and/or resilience. The optimization framework includes program analyses that characterize the accuracy of transformed programs, and search techniques that navigate the tradeoff space induced by transformations to find approximate programs with profitable tradeoffs. Our research shows that this approach can significantly improve program performance while providing acceptably accurate results.

关键词： optimisation program diagnostics search problems accuracy-aware optimization accuracy-aware program transformations approximate programs energy efficiency profitable tradeoffs program analyses program optimizations search techniques tradeoff space Accuracy Approximation methods Computational efficiency Hardware optimization Probabilistic logic programming analysis programme search technique Probabilistic logic tabu search Approximation method Computational efficiency Computer hardware Energy efficiency programming program optimization

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Making Collection Operations Optimal with Aggressive JIT Compilation 8

Making Collection Operations Optimal with Aggressive JIT Com...

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8th ACM SIGPLAN International Symposium on Scala (SCALA)

作者： Prokopec, Aleksandar Leopoldseder, David Duboscq, Gilles Wuerthinger, Thomas Oracle Labs Zurich Switzerland Johannes Kepler Univ Linz Linz Austria

ISBN: (纸本)9781450355292

Functional collection combinators are a neat and widely accepted data processing abstraction. However, their generic nature results in high abstraction overheads - Scala collections are known to be notoriously slow for typical tasks. We show that proper optimizations in a JIT compiler can widely eliminate overheads imposed by these abstractions. Using the open-source Graal JIT compiler, we achieve speedups of up to 20x on collection workloads compared to the standard HotSpot C2 compiler. Consequently, a sufficiently aggressive JIT compiler allows the language compiler, such as Scalac, to focus on other concerns. In this paper, we show how optimizations, such as inlining, polymorphic inlining, and partial escape analysis, are combined in Graal to produce collections code that is optimal with respect to manually written code, or close to optimal. We argue why some of these optimizations are more effectively done by a JIT compiler. We then identify specific usecases that most current JIT compilers do not optimize well, warranting special treatment from the language compiler.

关键词： collections data-parallelism program optimization JIT compilation functional combinators partial escape analysis iterators inlining scalar replacement

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Optimizing Database-Backed Applications with Query Synthesis

Optimizing Database-Backed Applications with Query Synthesis

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34th ACM SIGPLAN Conference on programming Language Design and Implementation (PLDI)

作者： Cheung, Alvin Solar-Lezama, Armando Madden, Samuel MIT CSAIL United States

ISBN: (纸本)9781450320146

Object-relational mapping libraries are a popular way for applications to interact with databases because they provide transparent access to the database using the same language as the application. Unfortunately, using such frameworks often leads to poor performance, as modularity concerns encourage developers to implement relational operations in application code. Such application code does not take advantage of the optimized relational implementations that database systems provide, such as efficient implementations of joins or push down of selection predicates. In this paper we present QBS, a system that automatically transforms fragments of application logic into SQL queries. QBS differs from traditional compiler optimizations as it relies on synthesis technology to generate invariants and postconditions for a code fragment. The postconditions and invariants are expressed using a new theory of ordered relations that allows us to reason precisely about both the contents and order of the records produced complex code fragments that compute joins and aggregates. The theory is close in expressiveness to SQL, so the synthesized postconditions can be readily translated to SQL queries. Using 75 code fragments automatically extracted from over 120k lines of open-source code written using the Java Hibernate ORM, we demonstrate that our approach can convert a variety of imperative constructs into relational specifications and significantly improve application performance asymptotically by orders of magnitude.

关键词： program optimization program synthesis performance

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Floating-Point Precision Tuning Using Blame Analysis 16

Floating-Point Precision Tuning Using Blame Analysis

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38th IEEE/ACM International Conference on Software Engineering (ICSE)

作者： Rubio-Gonzalez, Cindy Cuong Nguyen Mehne, Benjamin Sen, Koushik Demmel, James Kahan, William Iancu, Costin Lavrijsen, Wim Bailey, David H. Hough, David Univ Calif Davis Davis CA 95616 USA Univ Calif Berkeley Berkeley CA 94720 USA Lawrence Berkeley Natl Lab Berkeley CA USA Oracle Corp Redwood Shores CA USA

ISBN: (纸本)9781450339001

While tremendously useful, automated techniques for tuning the precision of floating-point programs face important scalability challenges. We present Blame Analysis, a novel dynamic approach that speeds up precision tuning. Blame Analysis performs floating-point instructions using different levels of accuracy for their operands. The analysis determines the precision of all operands such that a given precision is achieved in the final result of the program. Our evaluation on ten scientific programs shows that Blame Analysis is successful in lowering operand precision. As it executes the program only once, the analysis is particularly useful when targeting reductions in execution time. In such case, the analysis needs to be combined with search-based tools such as Precimonious. Our experiments show that combining Blame Analysis with Precimonious leads to obtaining better results with significant reduction in analysis time: the optimized programs execute faster (in three cases, we observe as high as 39.9% program speedup) and the combined analysis time is 9x faster on average, and up to 38x faster than Precimonious alone.

关键词： floating point mixed precision program optimization

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Identification of Approximable program Components Using Edge Profiling 1st

Identification of Approximable Program Components Using Edge...

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1st International Conference on Electronic Systems and Intelligent Computing, ESIC 2020

作者： Arundhati, Priya Pani, Santosh Kumar School of Computer Engineering KIIT University Bhubaneswar India

ISBN: (纸本)9789811570308

Approximate computing is gaining popularity day-by-day due to its growing application area. One of the areas where it is required to give attention is program analysis techniques. program analysis focuses mainly on program optimization and the correctness of the program. For program optimization, some transformation in the source code is carried out. In this paper, we have proposed a novel idea for transforming a normal program into an approximated program. The approximated version of the program can run in the non-approximated hardware and can decrease computation time, resource utilization, memory uses, and power consumption. Our method finds the cold segment of the original program by using Eege profiling and apply approximation as these parts have less effect on the final output value. The use of the distortion metric verifies the output quality of our transformation. © 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Approximate program transformation Distortion Edge profiling program optimization

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ACC Saturator: Automatic Kernel optimization for Directive-Based GPU Code

ACC Saturator: Automatic Kernel Optimization for Directive-B...

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2024 Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Matsumura, Kazuaki De Gonzalo, Simon Garcia Pena, Antonio J. Spain Sandia National Laboratories United States

ISBN: (纸本)9798350355543

Automatic code optimization is a complex process that typically involves the application of multiple discrete algorithms that modify the program structure irreversibly. However, the design of these algorithms is often monolithic, and they require repetitive implementation to perform similar analyses due to the lack of cooperation. To address this issue, modern optimization techniques, such as equality saturation, allow for exhaustive term rewriting at various levels of inputs, thereby simplifying compiler *** this paper, we propose equality saturation to optimize sequential codes utilized in directive-based programming for GPUs. Our approach realizes less computation, less memory access, and high memory throughput simultaneously. Our fully-automated framework constructs single-assignment forms from inputs to be entirely rewritten while keeping dependencies and extracts optimal cases. Through practical benchmarks, we demonstrate a significant performance improvement on several compilers. Furthermore, we highlight the advantages of computational reordering and emphasize the significance of memory-access order for modern GPUs. © 2024 IEEE.

关键词： Code Generation Compiler Directive-Based programming GPUs program optimization

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A Termination Condition of Unfolding Loop for Generalized Partial Computation

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The Journal of China Universities of Posts and Telecommunications 2001年第2期8卷 25-31,39页

作者： ZHAO Dong fan, FU Yan ning (Department of Computer Science and Technology, Jilin University, Changchun 130012, P.R. China) Department of Computer Science and Technology Jilin University

The unfolding problem of loop has always been a difficult problem on the partial computation and Generalized Partial Computation( GPC ) of imperative language. This paper makes use of Data Flow Analysis( DFA ) technique to present an efficient termination condition of unfolding loop for partial evaluation or generalized partial evaluation, and this termination condition can solve the problem very well.

关键词： program analysis DFA program optimization partial computation

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Theorem Proving for All: Equational Reasoning in Liquid Haskell (Functional Pearl) 11

Theorem Proving for All: Equational Reasoning in Liquid Hask...

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Haskell Conference

作者： Vazou, Niki Breitner, Joachim Kunkel, Rose Van Horn, David Hutton, Graham Univ Maryland College Pk MD 20742 USA Univ Penn Philadelphia PA 19104 USA Univ Nottingham Nottingham England

ISBN: (纸本)9781450358354

Equational reasoning is one of the key features of pure functional languages such as Haskell. To date, however, such reasoning always took place externally to Haskell, either manually on paper, or mechanised in a theorem prover. This article shows how equational reasoning can be performed directly and seamlessly within Haskell itself, and be checked using Liquid Haskell. In particular, language learners - to whom external theorem provers are out of reach - can benefit from having their proofs mechanically checked. Concretely, we show how the equational proofs and derivations from Hutton's textbook can be recast as proofs in Haskell (spoiler: they look essentially the same).

关键词： Liquid Haskell theorem proving Haskell equational reasoning program optimization

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