Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/132114
Title: GPU PERFORMANCE MODELLING AND OPTIMIZATION
Authors: LI ANG
Keywords: GPU, Performance Modeling, Optimization, Computer Architecture, High Performance Computing, Approximate Computing
Issue Date: 11-Jul-2016
Source: LI ANG (2016-07-11). GPU PERFORMANCE MODELLING AND OPTIMIZATION. ScholarBank@NUS Repository.
Abstract: The last decade has witnessed the blooming emergence of general-purpose Graphic-Processing-Unit computing (GPGPU). With the exponential growth of cores and threads in a modern GPU processor, how to analyze and optimize its performance becomes a grand challenge. In this thesis, as the modeling part, we propose an analytic model for throughput-oriented parallel processors. The model is visualizable, traceable and portable, while providing a good abstraction for both application designers and hardware architects to understand the performance and motivate potential optimization approaches. As the optimization part, we focus on each crucial component of a GPU streaming-multiprocessor, in particular registers-files, compute-units (SPU, DPU, SFU), caches (L1, L2, read-only, texture, constant) and scratchpad memory alternatively, clarify its underlying performance tradeoffs, and propose effective solutions to handle the tradeoffs in the design space. All the proposed optimization approaches are purely software-based. They are adaptive, transparent, traceable and portable, which leads to achievable and immediate performance gains for various existing GPU devices, especially for GPU integrated high-performance-computers (HPC).
URI: http://scholarbank.nus.edu.sg/handle/10635/132114
Appears in Collections:Ph.D Theses (Open)

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