Spatial instruction scheduling for raw machines

Instruction scheduling on software exposed architectures, such as Raw, must be performed in both time and space. The complexity and variance of application scheduling regions dictates that the space-time scheduling task be divided into phases. Unfortunately, the interaction of phases presents a phase ordering problem. In this thesis, the structure of program scheduling regions is studied. The scheduling regions are shown to have varying characteristics that are too diverse for a single simple algorithm to cover. A new scheduling technique is proposed to cope with this diversity and minimize the phase ordering problem. First, rather than maintaining exact mappings of instructions to time and space, the internal state of the scheduler maintains probabilities for different assignments of instructions to time and space resources. Second, a set of small scheduling heuristics cooperatively iterate over the probabilistic assignments many times in order to minimize the effects of phase ordering. A simple spatial instruction scheduler for Raw machines based on this technique is implemented and shown to outperform existing spatial scheduling systems on average.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2002

Author dc:creator

• Swenson, Shane Michael, 1979-

Advisor dc:contributor.advisor

• Saman Amarasinghe.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

en_US

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/28620

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/28620