Many modern compilers implement function calls (or returns) in two steps: first, a closure environment is properly installed to provide access for free variables in the target program fragment; second, the control is transferred to the target by a "jump with arguments (or results)." Closure conversion, which decides where and how to represent closures at runtime, is a crucial step in compilation of functional languages. We have a new algorithm that exploits the use of compile-time control and data flow information to optimize closure representations. By extensive closure sharing and allocating as many closures in registers as possible, our new closure conversion algorithm reduces heap allocation by 36% and memory fetches for local/global variables by 43%; and improves the already-efficient code generated by the Standard ML of New Jersey compiler by about 17% on a DECstation 5000. Moreover, unlike most other approaches, our new closure allocation scheme satisfies the strong "safe for sp...

Two strategies for supporting asynchronous interrupts are: the use of the processor's hardware interrupt system and the use of polling. The advantages of polling include: portability, simplicity, and low cost for handling interrupts. Unfortunately, polling has an overhead for the explicit interrupt checks inserted in the code. This paper describes balanced polling , a method for placing the interrupt checks which has a low overhead and also guarantees an upper bound on interrupt latency. This method has been used by Gambit (an optimizing native code compiler for Scheme) to support a number of features including multiprocessing and stack overflow detection. The overhead of balanced polling is less than for call-return polling which places interrupt checks at every procedure entry and exit. The overhead of call-return polling is typically 70% larger (but sometimes over 400% larger) than the overhead of balanced polling. 1 Introduction In this paper, the term interrupt is defined as an ...

Many language theoreticians have taken great efforts in designing higher-level programming languages that are more elegant and more expressive than conventional languages. However, few of these new languages have been implemented very efficiently. The result is that most software engineers still prefer to use conventional languages, even though the new higherlevel languages offer a better and simpler programming model. This dissertation concentrates on improving the performance of programs written in Standard ML (SML)---a statically typed functional language---on today's RISC machines. SML poses tough challenges to efficient implementations: very frequent function calls, polymorphic types, recursive data structures, higher-order functions, and first-class continuations. This dissertation presents the design and evaluation of several new compilation techniques that meet these challenges by taking advantage of some of the higher-level language features in SML. Type-directed compilation ...

Programs compiled by Gambit, our Scheme compiler, achieve performance as much as twice that of the fastest available Scheme compilers. Gambit is easily ported, while retaining its high performance, through the use of a simple virtual machine (PVM). PVM allows a wide variety of machineindependent optimizations and it supports parallel computation based on the future construct. PVM conveys high-level information bidirectionally between the machine-independent front end of the compiler and the machine-dependent back end, making it easy to implement a number of common back end optimizations that are difficult to achieve for other virtual machines. PVM is similar to many real computer architectures and has an option to efficiently gather dynamic measurements of virtual machine usage. These measurements can be used in performance prediction for ports to other architectures as well as design decisions related to proposed optimizations and object representations.

In this paper I present a set of conceptually simple but involved techniques used by Liar 1 , the MIT Scheme compiler, to generate good code when recursive procedures are specified in terms of suitable versions of the Y operator. The techniques presented are general-purpose analysis and optimization tools, similar to well-known techniques used in the analysis and optimization of applicative languages, that combine synergistically to enable Liar to generate identical machine code for ordinary recursive definitions written using letrec and those written using suitable forms of Y. 1 Introduction: The problem Modern programming languages allow programmers to write local recursive procedure definitions. Common Lisp [17] provides the labels special form for this purpose. Scheme [13] provides the similar letrec special form, as well as internal definitions, a syntactic alternative more akin to the internal procedure declarations of Algol-60 [6]. Recursive procedures are described, and s...