Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/30708
Title: A computing origami: Optimized code generation for emerging parallel platforms
Authors: HAGIESCU MIRISTE ANDREI MIHAI
Keywords: mapping, compilation, flexible, GPU, FPGA, StreamIt
Issue Date: 8-Aug-2011
Source: HAGIESCU MIRISTE ANDREI MIHAI (2011-08-08). A computing origami: Optimized code generation for emerging parallel platforms. ScholarBank@NUS Repository.
Abstract: This thesis deals with code generation for parallel applications on emerging platforms, in particular FPGA and GPU-based platforms. These platforms expose a large design space, throughout which performance is affected by significant architectural idiosyncrasies. In this context, generating efficient code is a global optimization problem. The code generation methods described in this thesis apply to applications which expose a flexible parallel structure that is not bound to the target platform. The application is restructured in a way which can be intuitively visualized as Origami (the Japanese art of paper folding). The thesis makes three significant contributions: (1) It provides code generation methods starting from a general stream processing language (StreamIt) for both FPGA and GPU platforms. (2) It describes how the code generation methods can be extended beyond streaming applications to finer-grained parallel computation. On FPGAs, this is illustrated by a method that generates configurable floating-point SIMD coprocessors for vectorizable code. On GPUs, the method is extended to applications which expose fine-grained parallel code accompanied by a significant amount of read sharing. (3) It shows how these methods can be used on a platform which consists of multiple GPU devices connected to a host CPU. The methods can be applied to a broad range of applications. They go beyond mapping and provide tightly integrated code generation tools that handle together high-level mapping, code rewriting, optimizations and modular compilation. These methods target FPGA and GPU platforms without requiring user-added annotations. The results indicate the efficiency of the methods described.
URI: http://scholarbank.nus.edu.sg/handle/10635/30708
Appears in Collections:Ph.D Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
HagiescuMiristeAM.pdf1.88 MBAdobe PDF

OPEN

NoneView/Download

Page view(s)

337
checked on Dec 11, 2017

Download(s)

419
checked on Dec 11, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.