. We have developed and implemented techniques that double the performance of dynamically-typed object-oriented languages. Our SELF implementation runs twice as fast as the fastest Smalltalk implementation, despite SELF's lack of classes and explicit variables. To compensate for the absence of classes, our system uses implementation-level maps to transparently group objects cloned from the same prototype, providing data type information and eliminating the apparent space overhead for prototype-based systems. To compensate for dynamic typing, user-defined control structures, and the lack of explicit variables, our system dynamically compiles multiple versions of a source method, each customized according to its receiver's map. Within each version the type of the receiver is fixed, and thus the compiler can statically bind and inline all messages sent to self. Message splitting and type prediction extract and preserve even more static type information, allowing the compiler to inline ma...

Object-oriented programming languages promise to improve programmer productivity by supporting abstract data types, inheritance, and message passing directly within the language. Unfortunately, traditional implementations of object-oriented language features, particularly message passing, have been much slower than traditional implementations of their non-object-oriented counterparts: the fastest existing implementation of Smalltalk-80 runs at only a tenth the speed of an optimizing C implementation. The dearth of suitable implementation technology has forced most object-oriented languages to be designed as hybrids with traditional non-object-oriented languages, complicating the languages and making programs harder to extend and reuse. This dissertation describes a collection of implementation techniques that can improve the run-time performance of object-oriented languages, in hopes of reducing the need for hybrid languages and encouraging wider spread of purely object-oriented langu...

Abstract. We have developed and implemented techniques that double the performance of dynamically-typed object-oriented languages. Our SELF implementation runs twice as fast as the fastest Smalltalk implementation, despite SELF’s lack of classes and explicit variables. To compensate for the absence of classes, our system uses implementation-level maps to transparently group objects cloned from the same prototype, providing data type information and eliminating the apparent space overhead for prototype-based systems. To compensate for dynamic typing, user-defined control structures, and the lack of explicit variables, our system dynamically compiles multiple versions of a source method, each customized according to its receiver’s map. Within each version the type of the receiver is fixed, and thus the compiler can statically bind and inline all messages sent to self. Message splitting and type prediction extract and preserve even more static type information, allowing the compiler to inline many other messages. Inlining dramatically improves performance and eliminates the need to hard-wire low-level methods such as +, ==, and ifTrue:. Despite inlining and other optimizations, our system still supports interactive programming environments. The system traverses internal dependency lists to invalidate all compiled methods

Dynamically-dispatched calls often limit the performance of object-oriented programs since object-oriented programming encourages factoring code into small, reusable units, thereby increasing the frequency of these expensive operations. Frequent calls not only slow down execution with the dispatch overhead per se, but more importantly they hinder optimization by limiting the range and effectiveness of standard global optimizations. In particular, dynamicallydispatched calls prevent standard interprocedural optimizations that depend on the availability of a static call graph. The SELF implementation described here offers two novel approaches to optimization. Type feedback speculatively inlines dynamically-dispatched calls based on profile information that predicts likely receiver classes. Adaptive optimization reconciles optimizing compilation with interactive performance by incrementally optimizing only the frequently-executed parts of a program. When combined, these two techniques result in a system that can execute programs significantly faster than previous systems while retaining much of the interactiveness of an interpreted system.

Instruction Set. An assembler for this instruction set was built, and a number of programs written to evaluate the architecture and to test ideas. Ideas and results from this abstract machine were used in the design of the real hardware, and the implementation of the simulator assisted in the design of the later simulator and other software tools. 2.5.7 Other Issues Both technological and architectural improvements to conventional RISC processors have been progressing at a phenomenal rate. The resulting performance is considerable and still improving rapidly, with techniques such as "superscalar " architectures and instruction-level parallelism being introduced into production workstation systems. This has allowed VM-based implementations of Smalltalk, such as PS, to have gained in performance during the period of the project. Raw performance cannot be the aim of a single prototype machine; instead, architectural effectiveness, or the performance to clock period ratio, is the impor...