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

# Contributions

The optimizations provided by MLRISC are at a similar level to those performed by the Impact compiler; several target back ends exist (Dec Alpha, HPPA, Sparc, x86, and PPC); but more importantly, the framework has been demonstrated in real use for languages with radically different execution models. These include:

Compiler | Association
SML/NJ | Bell Labs and Princeton
TIL | CMU
Tiger | Princeton
C-- | OGI
SML/Regions | DIKU
Moby | Bell Labs

The strength of MLRISC lies in the ability to easily create high quality code generator for each of these systems. For example:

Tiger:
  Has an execution model very similar to C with stack allocated activation frames, and also maintains static and dynamic chains to support lexical scoping.

TIL:
  Is similar to C in its use of activation frames, however it uses a typed intermediate language that supports almost tag-free garbage collection. This has severe implications on the interaction of spilling and garbage collection. The set of live variables and their locations, be it registers or frame slots, is recorded in a trace table for a specific program point. When spilling occurs, it is necessary to adjust some of these trace tables to reflect the new locations of live variables.

SML/NJ:
  Has no runtime stack, but stores all execution context in a garbage collected heap. This arrangement imposes special requirements for spilling registers. SML/NJ also does dynamic linking --- that is to say, no use is made of a conventional linker, but machine code is generated directly and linked into the interactive environment, dynamically.

C--:
  Is a C-like portable assembly language used as an intermediate language for high level typed language, and provides direct compilation support for exceptions and precise garbage collection. In addition, it allows interoperability with C function calls.

It is not uncommon for any of these systems to store special global values in dedicated registers, and use their own parameter passing and callee-save conventions. In any language that supports garbage collection, there are also the issues of generating gc type maps, and gc-safety in aggressive optimizations. MLRISC deals with all these important issues by allowing customization of many aspects of the system.

Lal George
Allen Leung

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Last modified: Fri Oct 11 18:19:52 UTC 2019 by buildd@x86-grnet-02