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compiler-directed file layout optimization for hierarchical storage systems

SCIENTIFIC PROGRAMMING 2013年第3-4期21卷 65-78页

作者： Ding, Wei Zhang, Yuanrui Kandemir, Mahmut Son, Seung Woo Penn State Univ University Pk PA 16802 USA Intel Corp University Pk PA USA Northwestern Univ Evanston IL USA

File layout of array data is a critical factor that effects the behavior of storage caches, and has so far taken not much attention in the context of hierarchical storage systems. The main contribution of this paper is a compiler-driven file layout optimization scheme for hierarchical storage caches. This approach, fully automated within an optimizing compiler, analyzes a multi-threaded application code and determines a file layout for each disk-resident array referenced by the code, such that the performance of the target storage cache hierarchy is maximized. We tested our approach using 16 I/O intensive application programs and compared its performance against two previously proposed approaches under different cache space management schemes. Our experimental results show that the proposed approach improves the execution time of these parallel applications by 23.7% on average.

关键词： File layout compiler optimization

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Evolutionary optimization of compiler Flag Selection by Learning and Exploiting Flags Interactions

Evolutionary Optimization of Compiler Flag Selection by Lear...

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Genetic and Evolutionary Computation Conference (GECCO)

作者： Garciarena, Unai Santana, Roberto Univ Basque Country UPV EHU Fac Informat Leioa Spain Univ Basque Country UPV EHU Intelligent Syst Grp Leioa Spain

ISBN: (纸本)9781450343237

compiler flag selection can be an effective way to increase the quality of executable code according to different code quality criteria. Evolutionary algorithms have been successfully applied to this optimization problem. However, previous approaches have only partially addressed the question of capturing and exploiting the interactions between compilation options to improve the search. In this paper we deal with this question comparing estimation of distribution algorithms (EDAs) and a traditional genetic algorithm approach. We show that EDAs that learn bivariate interactions can improve the results of GAs for some of the programs considered. We also show that the probabilistic models generated as a result of the search for optimal flag combinations can be used to unveil the (problem-dependent) interactions between the flags, allowing the user a more informed choice of compilation options.

关键词： compiler flag selection compiler optimization probabilistic modeling EDAs

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OpenMP to GPGPU: A compiler Framework for Automatic Translation and optimization

OpenMP to GPGPU: A Compiler Framework for Automatic Translat...

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14th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

作者： Lee, Seyong Min, Seung-Jai Eigenmann, Rudolf Purdue Univ Sch ECE W Lafayette IN 47907 USA

ISBN: (纸本)9781605583976

GPGPUs have recently emerged as powerful vehicles for general-purpose high-performance computing. Although a new Compute Unified Device Architecture (CUDA) programming model from NVIDIA offers improved programmability for general computing, programming GPGPUs is still complex and error-prone. This paper presents a compiler framework for automatic source-to-source translation of standard OpenMP applications into CUDA-based GPGPU applications. The goal of this translation is to further improve programmability and make existing OpenMP applications amenable to execution on GPGPUs. In this paper, we have identified several key transformation techniques, which enable efficient GPU global memory access, to achieve high performance. Experimental results from two important kernels (JACOBI and SPMUL) and two NAS OpenMP Parallel Benchmarks (EP and CG) show that the described translator and compile-time optimizations work well on both regular and irregular applications, leading to performance improvements of up to 50X over the unoptimized translation (up to 328X over serial on a CPU).

关键词： Algorithms Design Performance OpenMP GPU CUDA Automatic Translation compiler optimization

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Linear and Non-linear Relational Analyses for Quantum Program optimization

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PROCEEDINGS OF THE ACM ON PROGRAMMING LANGUAGES-PACMPL 2025年第POPL期9卷 1072-1103页

作者： Amy, Matthew Lunderville, Joseph Simon Fraser Univ Burnaby BC Canada

The phase folding optimization is a circuit optimization used in many quantum compilers as a fast and effective way of reducing the number of high-cost gates in a quantum circuit. However, existing formulations of the optimization rely on an exact, linear algebraic representation of the circuit, restricting the optimization to being performed on straightline quantum circuits or basic blocks in a larger quantum program. We show that the phase folding optimization can be re-cast as an affine relation analysis, which allows the direct application of classical techniques for affine relations to extend phase folding to quantum programs with arbitrarily complicated classical control flow including nested loops and procedure calls. Through the lens of relational analysis, we show that the optimization can be powered-up by substituting other classical relational domains, particularly ones for non-linear relations which are useful in analyzing circuits involving classical arithmetic. To increase the precision of our analysis and infer non-linear relations from gate sets involving only linear operations - such as Clifford+T - we show that the sum-over-paths technique can be used to extract precise symbolic transition relations for straightline circuits. Our experiments show that our methods are able to generate and use non-trivial loop invariants for quantum program optimization, as well as achieve some optimizations of common circuits which were previously attainable only by hand.

关键词： Quantum software compiler optimization data flow analysis relational program analysis invariant generation

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Revealing compiler Heuristics through Automated Discovery and optimization 24

Revealing Compiler Heuristics through Automated Discovery an...

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22nd IEEE/ACM International Symposium on Code Generation and optimization (CGO)

作者： Seeker, Volker Cummins, Chris Cole, Murray Franke, Bjorn Hazelwood, Kim Leather, Hugh Meta AI Menlo Pk CA 94025 USA Univ Edinburgh Edinburgh Midlothian Scotland

ISBN: (纸本)9798350395099

Tuning compiler heuristics and parameters is well known to improve optimization outcomes dramatically. Prior works have tuned command line flags and a few expert identified heuristics. However, there are an unknown number of heuristics buried, unmarked and unexposed inside the compiler as a consequence of decades of development without auto-tuning being foremost in the minds of developers. Many may not even have been considered heuristics by the developers who wrote them. The result is that auto-tuning search and machine learning can optimize only a tiny fraction of what could be possible if all heuristics were available to tune. Manually discovering all of these heuristics hidden among millions of lines of code and exposing them to auto-tuning tools is a Herculean task that is simply not practical. What is needed is a method of automatically finding these heuristics to extract every last drop of potential optimization. In this work, we propose Heureka, a framework that automatically identifies potential heuristics in the compiler that are highly profitable optimization targets and then automatically finds available tuning parameters for those heuristics with minimal human involvement. Our work is based on the following key insight: When modifying the output of a heuristic within an acceptable value range, the calling code using that output will still function correctly and produce semantically correct results. Building on that, we automatically manipulate the output of potential heuristic code in the compiler and decide using a Differential Testing approach if we found a heuristic or not. During output manipulation, we also explore acceptable value ranges of the targeted code. Heuristics identified in this way can then be tuned to optimize an objective function. We used Heureka to search for heuristics among eight thousand functions from the LLVM optimization passes, which is about 2% of all available functions. We then use identified heuristics to tune the compila

关键词： Terms-Search Methodologies compiler optimization Differential Testing

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Efficient compiler Autotuning via Bayesian optimization 21

Efficient Compiler Autotuning via Bayesian Optimization

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43rd IEEE/ACM International Conference on Software Engineering - Software Engineering in Practice (ICSE-SEIP) / 43rd ACM/IEEE International Conference on Software Engineering - New Ideas and Emerging Results (ICSE-NIER)

作者： Chen, Junjie Xu, Ningxin Chen, Peiqi Zhang, Hongyu Tianjin Univ Coll Intelligence & Comp Tianjin Peoples R China Univ Newcastle Callaghan NSW Australia

ISBN: (纸本)9780738113197

A typical compiler such as GCC supports hundreds of optimizations controlled by compilation Rags for improving the runtime performance of the compiled program. Due to the large number of compilation nags and the exponential number of flag combinations, it is impossible for compiler users to manually tune these optimization flags in order to achieve the required runtime performance of the compiled programs. Over the years, many compiler autotuning approaches have been proposed to automatically tune optimization flags, but they still suffer from the efficiency problem due to the huge search space. In this paper, we propose the first Bayesian optimization based approach, called BOCA, for efficient compiler autotuning. In BOCA, we leverage a tree-based model for approximating the objective function in order to make Bayesian optimization scalable to a large number of optimization Hags. Moreover, we design a novel searching strategy to improve the efficiency of Bayesian optimization by incorporating the impact of each optimization flag measured by the tree-based model and a decay function to strike a balance between exploitation and exploration. We conduct extensive experiments to investigate the effectiveness of BOCA on two most popular C compilers (i.e.. GCC and LLVM) and two widely-used C benchmarks (i.e., cBench and PolyBench). The results show that BOCA significantly outperforms the state-of-the-art compiler autotuning approaches and Bayesion optimization methods in terms of the time spent on achieving specified speedups, demonstrating the effectiveness of BOCA.

关键词： compiler Autotuning Bayesian optimization compiler optimization Configuration

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Annotation of compiler Attributes for MPI Functions 31st

Annotation of Compiler Attributes for MPI Functions

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31st European MPI Users' Group Meeting (EuroMPI)

作者： Jammer, Tim Schmidt, Adrian Bischof, Christian Tech Univ Darmstadt Darmstadt Germany

ISBN: (纸本)9783031733697;9783031733703

This paper explores the use of LLVM IR function and parameter attributes to enhance compiler optimizations for code that uses MPI. As MPI is usually used as a dynamically linked library, the compiler is not able to automatically infer certain function attributes like nofree, which signals that no memory is deallocated in this function. Therefore, we implemented an LLVM compiler pass that annotates the used MPI functions with suitable attributes when compiling the user application. We manually derived applicable attributes based on the semantics described in the MPI standard, so that this approach is applicable to all MPI implementations. We showcase different cases where this additional annotations impact the code generated by the compiler for the MiniApps from the Exascale Proxy Applications Project. The addition of MPI function annotations allows for a variety of compiler optimizations like reducing unnecessary memory accesses, optimizing register usage, and streamlining control flow. The code of our annotation pass is available on GitHub: https:// ***/AdrSchm/mpi- attributes-pass.

关键词： MPI compiler analysis compiler optimization function attributes

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Investigating the superiority of Intel oneAPI IFX compiler on Intel CPUs using different optimization levels: A case study on a CFD system 4

Investigating the superiority of Intel oneAPI IFX compiler o...

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4th IEEE Global Conference for Advancement in Technology, GCAT 2023

作者： Alaswad, Feisal Eswaran, Poovammal Department of Computing Technologies SRM Institute of Science and Technology Kattankulathur Chennai India

ISBN: (纸本)9798350305258

Computational fluid dynamics (CFD) simulations are crucial in scientific and engineering domains. The compiler choice impacts CFD application performance, especially on specific processor architectures. This research compares the performance of a Fortran-based CFD system compiled with Intel OneAPI IFX against other commonly used compilers on Intel CPUs. Intel's OneAPI IFX compiler is designed for Intel CPUs and offers advanced optimizations. A Typical Fortran CFD system was used for the study, compiling it with IFX, Gfortran, NAG, and PGI compilers. Performance indicators, including execution time, memory usage, and computational precision, were collected. Our research findings revealed that the IFX compiler regularly outperforms the other compilers on Intel CPUs. This research underscores the significant performance benefits of employing the IFX compiler to compile Fortran-based CFD systems. IFX compiler achieves high decimal precision, reaching up to 15 decimal digits, and it also excels in time execution. Compared to other compilers like NAG, PGI, and GFortran, the OneAPI IFX compiler demonstrates notable improvements in execution time, with a 7.7% enhancement without code optimization and up to 3.7% with maximum code optimization on the Ubuntu operating system and with a 38.4% enhancement without code optimization and up to 30.8% with maximum code optimization on the Windows operating system. These findings highlight the superior performance and efficiency of the IFX compiler, making it a compelling choice for optimizing CFD simulations. The IFX compiler is recommended for CFD researchers and professionals to optimize Fortran-based CFD codes for better simulation performance and quicker time-to-solution, specifically on Intel hardware. © 2023 IEEE.

关键词： compiler optimization Computational fluid dynamics Heterogeneous Computing High-Performance Computing Intel OneAPI IFX

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compiler optimizations as a Countermeasure against Side-Channel Analysis in MSP430-Based Devices

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SENSORS 2012年第6期12卷 7994-8012页

作者： Malagon, Pedro de Goyeneche, Juan-Mariano Zapater, Marina Moya, Jose M. Bankovic, Zorana Univ Politecn Madrid Escuela Tecn Super Ingn Telecomunicac E-28040 Madrid Spain

Ambient Intelligence (AmI) requires devices everywhere, dynamic and massively distributed networks of low-cost nodes that, among other data, manage private information or control restricted operations. MSP430, a 16-bit microcontroller, is used in WSN platforms, as the TelosB. Physical access to devices cannot be restricted, so attackers consider them a target of their malicious attacks in order to obtain access to the network. Side-channel analysis (SCA) easily exploits leakages from the execution of encryption algorithms that are dependent on critical data to guess the key value. In this paper we present an evaluation framework that facilitates the analysis of the effects of compiler and backend optimizations on the resistance against statistical SCA. We propose an optimization-based software countermeasure that can be used in current low-cost devices to radically increase resistance against statistical SCA, analyzed with the new framework.

关键词： embedded system security side-channel attacks hiding countermeasure compiler optimization MSP430

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OpenMP to GPGPU: A compiler Framework for Automatic Translation and optimization

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ACM SIGPLAN NOTICES 2009年第4期44卷 101-110页

作者： Lee, Seyong Min, Seung-Jai Eigenmann, Rudolf Purdue Univ Sch ECE W Lafayette IN 47907 USA

关键词： Algorithms Design Performance OpenMP GPU CUDA Automatic Translation compiler optimization

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