MLRISC

MLRISC Contributors Requirements How to Obtain MLRISC

Overview

Problem Statement Contributions MLRISC Based Compiler MLRISC Intermediate Representation MLRisc Generation Back End Optimizations Register Allocation Machine Description Garbage Collection Safety System Integration Optimizations Graphical Interface Line Counts Systems Using MLRISC Future Work

System

Architecture of MLRISC The MLTREE Language MLTree Extensions MLTree Utilities Instruction Selection Assemblers Machine Code Emitters Delay Slot Filling Span Dependency Resolution The Graph Library The Graph Visualization Library Basic Compiler Graphs The MLRISC IR SSA Optimizations ILP Optimizations Optimizations for VLIW/EPIC Architectur... Register Allocator

Back Ends

The Alpha Back End The PA RISC Back End The Sparc Back End The Intel x86 Back End The PowerPC Back End The MIPS Back End The TI C6x Back End

Basic Types

Annotations Cells Cluster Client Defined Constants Client Defined Pseudo Ops Instructions Instruction Streams Label Expressions Labels Regions Regmap

# Problem Statement

Writing a native code generator for any language is a significant investment, especially for todays modern processors with require extensive compiler support to achieve high performance. The algorithms that must be used to generate high quality code are complex, sometimes quite delicate, and require substantial infrastructure.

A specific architecture has a relatively short life time in relation to the time taken to build the code generator, and one quickly needs the ability to retarget to new versions of the architecture, or to different target architectures. This is by no means an open problem. There are many compilers today that target multiple architectures, however the quality of code varies. For example, lcc by Chris Fraser and David Hansen does no back end optimizations; gcc from the Free Software Foundation does extensive peephole and simple data flow optimizations, and falls short on advanced superscalar optimizations; and finally the IMPACT compiler done by the Impact group at the University of Illinois specializes in more advanced superscalar and predicated architectures.

Assuming the retargeting issue is solved, one would like to use all the developed infrastructure for multiple source languages. This problem is far from solved; even though gcc has been used for multiple languages like Ada, Pascal, and Modula III, each of these have similiar execution models or were forced to adopt C conventions. gcc cannot be used directly for languages such as Lisp, Smalltalk, Haskell, or ML that have radically different execution models and special requirements to support advanced language features.

Lal George
Allen Leung

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Last modified: Mon Oct 3 20:52:35 UTC 2022 by buildd@x86-grnet-02