PEAK—a fast and effective performance tuning system via compiler optimization orchestration

Pan, Zhelong; Eigenmann, Rudolf

doi:10.1145/1353445.1353451

Cited by 27 publications

(13 citation statements)

References 57 publications

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“…Moreover, it is independent of the solution-space, the search algorithm and the compiler/optimizer used. PEAK, an automated performance tuning system is presented in [26]. It uses three heuristic algorithms to select good compiler optimization settings.…”

Section: Related Workmentioning

confidence: 99%

Use of Previously Acquired Positioning of Optimizations for Phase Ordering Exploration

Nobre

Martins

Cardoso

2015

Proceedings of the 18th International Workshop on Software and Compilers for Embedded Systems

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This paper presents a new approach to efficiently search for suitable compiler pass sequences, a challenge known as phase ordering. Our approach relies on information about the relative positions of compiler passes in compiler pass sequences previously generated for a set of functions when compiling for a specific processor. We enhanced two iterative compiler pass exploration schemes, one relying on simple sequential compiler pass insertion and other implementing an auto-tuned simulated annealing process, with a data structure that holds information about the relative positions of compiler sequences; in order to reduce the set of compiler passes considered for insertion in a given position of a given candidate compiler pass sequence to include only the passes that have a higher probability of performing well on that relative position in the compiler sequence, speeding up the exploration time as a result. We tested our approach with two different compilers and two different targets; the ReflectC and the LLVM compilers, targeting a MicroBlaze processor and a LEON3 processor, respectively. The experimental results show that we can considerably reduce the number of algorithm iterations by a factor of up to more than an order of magnitude when targeting the MicroBlaze or the LEON3, while finding compiler sequences that result in binaries that when executed on the target processor/simulator are able to outperform (i.e. use less CPU cycles) all the standard optimization levels (i.e., we compare against the most performing optimization level flag on each kernel, e.g. -O1, -O2 or -O3 in the case of LLVM) by a geometric mean performance improvement of 1.23x and 1.20x when targeting the MicroBlaze processor, and 1.94x and 2.65x when targetting the LEON3 processor; for each of the two exploration algorithms and two kernel sets considered.

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Section: Related Workmentioning

confidence: 99%

Use of Previously Acquired Positioning of Optimizations for Phase Ordering Exploration

Nobre

Martins

Cardoso

2015

Proceedings of the 18th International Workshop on Software and Compilers for Embedded Systems

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“…Moreover, it is independent of the solution-space, the search algorithm and the compiler/optimizer used. PEAK, an automated performance tuning system is presented in [35]. It uses three heuristic algorithms to select good compiler optimization settings.…”

Section: Related Workmentioning

confidence: 99%

Exploration of compiler optimization sequences using clustering-based selection

et al. 2014

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Due to the large number of optimizations provided in modern compilers and to compiler optimization specific opportunities, a Design Space Exploration (DSE) is necessary to search for the best sequence of compiler optimizations for a given code fragment (e.g., function). As this exploration is a complex and time consuming task, in this paper we present DSE strategies to select optimization sequences to both improve the performance of each function and reduce the exploration time. The DSE is based on a clustering approach which groups functions with similarities and then explore the reduced search space provided by the optimizations previously suggested for the functions in each group. The identification of similarities between functions uses a data mining method which is applied to a symbolic code representation of the source code. The DSE process uses the reduced set identified by clustering in two ways: as the design space or as the initial configuration. In both ways, the adoption of a pre-selection based on clustering allows the use of simple and fast DSE algorithms. Our experiments for evaluating the effectiveness of the proposed approach address the exploration of compiler optimization sequences considering 49 compilation passes and targeting a Xilinx MicroBlaze processor, and were performed aiming performance improvements for 41 functions. Experimental results reveal that the use of our new clustering-based DSE approach achieved a significant reduction on the total exploration time of the search space (18× over a Genetic Algorithm approach for DSE) at the same time that important performance speedups (43% over the baseline) were obtained by the optimized codes.

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“…Haneda et al employed statistical analysis of the effect of compiler options to prune the phase selection search space and find a single compiler setting for a collection of programs that performs better than the standard settings used in GCC [11]. Pan and Eigenmann developed three heuristic algorithms to quickly select good compiler optimization settings, and found that their combined approach that first identifies phases with negative performance effects and greedily eliminates them achieves the best result [22]. Also related is the work by Fursin et al who develop a GCC-based framework (MILEPOST GCC) to automatically extract program features and learn the best optimizations across programs.…”

Section: Background and Related Workmentioning

confidence: 99%

Performance potential of optimization phase selection during dynamic JIT compilation

Jantz

Kulkarni

2013

Proceedings of the 9th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments

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Phase selection is the process of customizing the applied set of compiler optimization phases for individual functions or programs to improve performance of generated code. Researchers have recently developed novel feature-vector based heuristic techniques to perform phase selection during online JIT compilation. While these heuristics improve program startup speed, steady-state performance was not seen to benefit over the default fixed single sequence baseline. Unfortunately, it is still not conclusively known whether this lack of steady-state performance gain is due to a failure of existing online phase selection heuristics, or because there is, indeed, little or no speedup to be gained by phase selection in online JIT environments. The goal of this work is to resolve this question, while examining the phase selection related behavior of optimizations, and assessing and improving the effectiveness of existing heuristic solutions.We conduct experiments to find and understand the potency of the factors that can cause the phase selection problem in JIT compilers. Next, using long-running genetic algorithms we determine that program-wide and method-specific phase selection in the HotSpot JIT compiler can produce ideal steady-state performance gains of up to 15% (4.3% average) and 44% (6.2% average) respectively. We also find that existing state-of-the-art heuristic solutions are unable to realize these performance gains (in our experimental setup), discuss possible causes, and show that exploiting knowledge of optimization phase behavior can help improve such heuristic solutions. Our work develops a robust open-source productionquality framework using the HotSpot JVM to further explore this problem in the future.

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PEAK—a fast and effective performance tuning system via compiler optimization orchestration

Cited by 27 publications

References 57 publications

Use of Previously Acquired Positioning of Optimizations for Phase Ordering Exploration

Use of Previously Acquired Positioning of Optimizations for Phase Ordering Exploration

Exploration of compiler optimization sequences using clustering-based selection

Performance potential of optimization phase selection during dynamic JIT compilation

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