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  1. Papers from the 1995 ACM SIGPLAN workshop on Intermediate representations (IR '95)
  2. Rationalized three instruction machine
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Incremental computation of dominator trees
A correspondence between continuation passing style and static single assignment form
GURRR: a global unified resource requirements representation
A simple graph-based intermediate representation
Optimizing sparse representations for dataflow analysis
Sparse functional stores for imperative programs
XIL and YIL: the intermediate languages of TOBEY
GC: the data-flow graph format of synchronous programming
Rationalized three instruction machine
Verification of ANDF components
Java intermediate bytecodes: ACM SIGPLAN workshop on intermediate representations (IR'95)
Clarity MCode: a retargetable intermediate representation for compilation

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Rationalized three instruction machine

Content Provider ACM Digital Library
Author Satpathy, Manoranjan Chitnis, Sachin V. Oberoi, Sundeep
Abstract The declarative nature of functional programming languages causes many difficulties in their efficient implementation on conventional machines. The problem is much harder when the language has non-strict (lazy) semantics. Abstract machines serve as an intellectual aid in bridging the semantic gap between such languages and the conventional von Neumann architecture. However they become more and more complex with time as efficiency considerations force the instruction set of the machine to grow in size. In this paper we explain the phenomenon in context of the Three Instruction Machine (TIM). We then define a rationalized instruction set for TIM that allows us to view all enhancements to TIM in a uniform way. This instruction set is quite close to RISC instructions and clearly identifies the key operations on closures. Translation of functional programs to our rationalized instruction set opens up scope for various local and global optimizations. We illustrate this by showing how to build control flow graphs and perform optimizations on it. Lazy arguments in functional programs make it hard to predict evaluation order statistically. We define the notion of pseudo-lazy arguments to statically expose the control flow information, wherever possible, for doing better flow analysis.
Starting Page 94
Ending Page 102
Page Count 9
File Format PDF
ISBN 0897917545
DOI 10.1145/202529.202539
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 1995-03-01
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Abstract machines Compiling and optimizations Functional programming Control flow analysis
Content Type Text
Resource Type Article
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