Compiler architecture using a portable intermediate language

The back end of a compiler performs machine-dependent tasks and low-level optimisations that are laborious to implement and difficult to debug. In addition, in languages that require run-time services such as garbage collection, the back end must interface with the run-time system to provide those services. The net result is that building a compiler back end entails a high implementation cost. In this dissertation I describe reusable code generation infrastructure that enables the construction of a complete programming language implementation (compiler and run-time system) with reduced effort. The infrastructure consists of a portable intermediate language, a compiler for this language and a low-level run-time system. I provide an implementation of this system and I show that it can support a variety of source programming languages, it reduces the overall eort required to implement a programming language, it can capture and retain information necessary to support run-time services and optimisations, and it produces efficient code

Future value based single assignment program representations and optimizations

An optimizing compiler internal representation fundamentally affects the clarity, efficiency and feasibility of optimization algorithms employed by the compiler. Static Single Assignment (SSA) as a state-of-the-art program representation has great advantages though still can be improved. This dissertation explores the domain of single assignment beyond SSA, and presents two novel program representations: Future Gated Single Assignment (FGSA) and Recursive Future Predicated Form (RFPF). Both FGSA and RFPF embed control flow and data flow information, enabling efficient traversal program information and thus leading to better and simpler optimizations. We introduce future value concept, the designing base of both FGSA and RFPF, which permits a consumer instruction to be encountered before the producer of its source operand(s) in a control flow setting. We show that FGSA is efficiently computable by using a series T1/T2/TR transformation, yielding an expected linear time algorithm for combining together the construction of the pruned single assignment form and live analysis for both reducible and irreducible graphs. As a result, the approach results in an average reduction of 7.7%, with a maximum of 67% in the number of gating functions compared to the pruned SSA form on the SPEC2000 benchmark suite. We present a solid and near optimal framework to perform inverse transformation from single assignment programs. We demonstrate the importance of unrestricted code motion and present RFPF. We develop algorithms which enable instruction movement in acyclic, as well as cyclic regions, and show the ease to perform optimizations such as Partial Redundancy Elimination on RFPF

Optimizations using global code motion for Java just-in-time compilers

制度:新 ; 文部省報告番号:乙1877号 ; 学位の種類:博士(情報科学) ; 授与年月日:2004/3/4 ; 早大学位記番号:新380

Cost-Optimal Code Motion

We generalize Knoop et al.’s Lazy Code Motion (LCM) algorithm for partial redundancy elimination so that the generalized version also performs strength reduction. Although Knoop et al. have themselves extended LCM to strength reduction with their Lazy Strength Reduction algorithm, our approach differs substantially from theirs and results in a broader class of candidate expressions, stronger safety guarantees, and the elimination of the potential for performance loss instead of gain. Also, our general framework is not limited to traditional strength reduction, but rather can also handle a wide variety of optimizations in which data-flow information enables the replacement of a computation with a less expensive one. As a simple example, computations can be hoisted to points where they are constant foldable. Another example we sketch is the hoisting of polymorphic operations to points where type analysis provides leverage for optimization. Our general approach consists of placing computations so as to minimize their cost, rather than merely their number. So long as the cost differences between flowgraph nodes obey a certain natural constraint, a cost-optimal code motion transformation that does not unnecessarily prolong the lifetime of temporary variables can be found using techniques completely analogous to LCM. Specifically, the cost differences can be discovered using a wide variety of forward data-flow analyses in a manner which we describe