NDLI: Optimizing ML with run-time code generation

Content Provider	ACM Digital Library
Author	Lee, Peter Leone, Mark
Abstract	We describe the design and implementation of a compiler that automatically translates ordinary programs written in a subset of ML into code that generates native code at run time. Run-time code generation can make use of values and invariants that cannot be exploited at compile time, yielding code that is often superior to statically optimal code. But the cost of optimizing and generating code at run time can be prohibitive. We demonstrate how compile-time specialization can reduce the cost of run-time code generation by an order of magnitude without greatly affecting code quality. Several benchmark programs are examined, which exhibit an average cost of only six cycles per instruction generated at run time.
Starting Page	137
Ending Page	148
Page Count	12
File Format	PDF
ISBN	0897917952
DOI	10.1145/231379.231407
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1996-05-01
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Optimizing ML with run-time code generation