کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
523792 868493 2016 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
The landscape of GPGPU performance modeling tools
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
The landscape of GPGPU performance modeling tools
چکیده انگلیسی


• Sketch and taxonomies of current performance modeling landscape for GPGPU.
• A thorough description of 10 different approaches to GPU performance modeling.
• Empirical evaluation of models’ performance using three kernels and four GPUs.
• Discussion of the strengths and weaknesses of the studied model classes.

GPUs are gaining fast adoption as high-performance computing architectures, mainly because of their impressive peak performance. Yet most applications only achieve small fractions of this performance. While both programmers and architects have clear opinions about the causes of this performance gap, finding and quantifying the real problems remains a topic for performance modeling tools. In this paper, we sketch the landscape of modern GPUs’ performance limiters and optimization opportunities, and dive into details on modeling attempts for GPU-based systems. We highlight the specific features of the relevant contributions in this field, along with the optimization and design spaces they explore. We further use typical kernel examples with various computation and memory access patterns to assess the efficacy and usability of a set of promising approaches. We conclude that the available GPU performance modeling solutions are very sensitive to applications and platform changes, and require significant efforts for tuning and calibration when new analyses are required.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Parallel Computing - Volume 56, August 2016, Pages 18–33
نویسندگان
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