This paper proposes an efficient technique for contextsensitive pointer analysis that is applicable to real C programs. For efficiency, we summarize the effects of procedures using partial transfer functions. A partial transfer function (PTF) describes the behavior of a procedure assuming that certain alias relationships hold when it is called. We can reuse a PTF in many calling contexts as long as the aliases among the inputs to the procedure are the same. Our empirical results demonstrate that this technique is successful---a single PTF per procedure is usually sufficient to obtain completely context-sensitive results. Because many C programs use features such as type casts and pointer arithmetic to circumvent the high-level type system, our algorithm is based on a low-level representation of memory locations that safely handles all the features of C. We have implemented our algorithm in the SUIF compiler system and we show that it runs efficiently for a set of C benchmarks. 1 Introd...

We present practical approximation methods for computing interprocedural aliases and side effects for a program written in a language that includes pointers, reference parameters and recursion. We present the following results: 1) An algorithm for flow-sensitive interprocedural alias analysis which is more precise and efficient than the best interprocedural method known. 2) An extension of traditional flow-insensitive alias analysis which accommodates pointers and provides a framework for a family of algorithms which trade off precision for efficiency. 3) An algorithm which correctly computes side effects in the presence of pointers. Pointers cannot be correctly handled by conventional methods for side effect analysis. 4) An alias naming technique which handles dynamically allocated objects and guarantees the correctness of data-flow analysis. 5) A compact representation based on transitive reduction which does not result in a loss of precision and improves precision in some cases. 6)...

This paper describes both the techniques themselves and our experience building and using register allocators that incorporate them. It provides a detailed description of optimistic coloring and rematerialization. It presents experimental data to show the performance of several versions of the register allocator on a suite of FORTRAN programs. It discusses several insights that we discovered only after repeated implementation of these allocators. Categories and Subject Descriptors: D.3.4 [Programming Languages]: Processors---compi l ers , optimization General terms: Languages Additional Key Words and Phrases: Register allocation, code generation, graph coloring 1. INTRODUCTION The relationship between run-time performance and e#ective use of a machine's register set is well understood. In a compiler, the process of deciding which values to keep in registers at each point in the generated code is called register allocation. Value

Chaitin and his colleagues at IBM in Yorktown Heights built the first global register allocator based on graph coloring. This thesis describes a series of improvements and extensions to the Yorktown allocator. There are four primary results: Optimistic coloring Chaitin's coloring heuristic pessimistically assumes any node of high degree will not be colored and must therefore be spilled. By optimistically assuming that nodes of high degree will receive colors, I often achieve lower spill costs and faster code; my results are never worse. Coloring pairs The pessimism of Chaitin's coloring heuristic is emphasized when trying to color register pairs. My heuristic handles pairs as a natural consequence of its optimism. Rematerialization Chaitin et al. introduced the idea of rematerialization to avoid the expense of spilling and reloading certain simple values. By propagating rematerialization information around the SSA graph using a simple variation of Wegman and Zadeck's constant propag...

An important function of any register allocator is to target registers so as to eliminate copy instructions. Graph-coloring register allocation is an elegant approach to this problem. If the source and destination of a move instruction do not interfere, then their nodes can be coalesced in the interference graph. Chaitin's coalescing heuristic could make a graph uncolorable (i.e., introduce spills); Briggs et al. demonstrated a conservative coalescing heuristic that preserves colorability. But Briggs's algorithm is too conservative, and leaves too many move instructions in our programs. We show how to interleave coloring reductions with Briggs's coalescing heuristic, leading to an algorithm that is safe but much more aggressive. 1 Introduction Graph coloring is a powerful approach to register allocation and can have a significant impact on the execution of compiled code. A good register allocator does copy propagation, eliminating many move instructions by "coloring" the source tempor...

Array privatization is one of the most effective transformations for the exploitation of parallelism. In this paper, we present a technique for automatic array privatization. Our algorithm uses data flow analysis of array references to identify privatizable arrays intraprocedurally as well as interprocedurally. It employs static and dynamic resolution to determine the last value of a lived private array.We compare the result of automatic array privatization with that of manual array privatization and identify directions for future improvement. To enhance the effectiveness of our algorithm, wedevelop a goal directly technique to analysis symbolic variables in the present of conditional statements, loops and index arrays.

This paper presents a novel framework for the symbolic bounds analysis of pointers, array indices, and accessed memory regions. Our framework formulates each analysis problem as a system of inequality constraints between symbolic bound polynomials. It then reduces the constraint system to a linear program. The solution to the linear program provides symbolic lower and upper bounds for the values of pointer and array index variables and for the regions of memory that each statement and procedure accesses. This approach eliminates fundamental problems associated with applying standard xed-point approaches to symbolic analysis problems. Experimental results from our implemented compiler show that the analysis can solve several important problems, including static race detection, automatic parallelization, static detection of array bounds violations, elimination of array bounds checks, and reduction of the number of bits used to store computed values.

this paper we present a practical technique for detecting a broader class of linear induction variables than is usually recognized, as well as several other sequence forms, including periodic, polynomial, geometric, monotonic, and wrap-around variables. Our method is based on Factored Use-Def (FUD) chains, a demand-driven representation of the popular Static Single Assignment form. In this form, strongly connected components of the associated SSA graph correspond to sequences in the source program: we describe a simple yet efficient algorithm for detecting and classifying these sequences. We have implemented this algorithm in Nascent, our restructuring Fortran 90+ compiler, and we present some results showing the effectiveness of our approach.

Advances in modern cryptography coupled with rapid growth in processing and communication speeds make secure twoparty computation a realistic paradigm. Yet, thus far, interest in this paradigm has remained mostly theoretical. This paper introduces Fairplay [28], a full-fledged system that implements generic secure function evaluation (SFE). Fairplay comprises a high level procedural definition language called SFDL tailored to the SFE paradigm; a compiler of SFDL into a one-pass Boolean circuit presented in a language called SHDL; and Bob/Alice programs that evaluate the SHDL circuit in the manner suggested by Yao in [39]. This system enables us to present the first evaluation of an overall SFE in real settings, as well as examining its components and identifying potential bottlenecks. It provides a test-bed of ideas and enhancements concerning SFE, whether by replacing parts of it, or by integrating with it. We exemplify its utility by examining several alternative implementations of oblivious transfer within the system, and reporting on their effect on overall performance. 1

Symbolic Domain The objects in our abstract symbolic domain are canonical symbolic expressions. A canonical symbolic expression is a lexicographically ordered sequence of symbolic terms. Each symbolic term is in turn a pair of an integer coefficient and a sequence of pairs of pointers to program variables in the program symbol table and their exponents. The latter sequence is also lexicographically ordered. For example, the abstract value of the symbolic expression 2ij+3jk in an environment that i is bound to (1; (( " i ; 1))), j is bound to (1; (( " j ; 1))), and k is bound to (1; (( " k ; 1))) is ((2; (( " i ; 1); ( " j ; 1))); (3; (( " j ; 1); ( " k ; 1)))). In our framework, environment is the abstract analogous of state concept; an environment is a function from program variables to abstract symbolic values. Each environment e associates a canonical symbolic value e x for each variable x 2 V ; it is said that x is bound to e x. An environment might be represented by...