Object-oriented programming languages confer many benefits, including abstraction, which lets the programmer hide the details of an object’s implementation from the object’s clients. Unfortunately, crossing abstraction boundaries often incurs a substantial run-time overhead in the form of frequent procedure calls. Thus, pervasive use of abstraction, while desirable from a design standpoint, may be impractical when it leads to inefficient programs. Aggressive compiler optimizations can reduce the overhead of abstraction. However, the long compilation times introduced by optimizing compilers delay the programming environment‘s responses to changes in the program. Furthermore, optimization also conflicts with source-level debugging. Thus, programmers are caught on the horns of two dilemmas: they have to choose between abstraction and efficiency, and between responsive programming environments and efficiency. This dissertation shows how to reconcile these seemingly contradictory goals by performing optimizations lazily. Four new techniques work together to achieve high performance and high responsiveness: • Type feedback achieves high performance by allowing the compiler to inline message sends based on information extracted from the runtime system. On average, programs run 1.5 times faster than the previous SELF system; compared to a commercial Smalltalk implementation, two medium-sized benchmarks run about three times faster. This level of performance is obtained with a compiler that is both simpler and faster than previous SELF compilers. • Adaptive optimization achieves high responsiveness without sacrificing performance by using a fast nonoptimizing compiler to generate initial code while automatically recompiling heavily used parts of the program with an optimizing compiler. On a previous-generation workstation like the SPARCstation-2, fewer than 200 pauses exceeded 200 ms during a 50-minute interaction, and 21 pauses exceeded one second. On a currentgeneration workstation, only 13 pauses exceed 400 ms. • Dynamic deoptimization shields the programmer from the complexity of debugging optimized code by transparently recreating non-optimized code as needed. No matter whether a program is optimized or not, it can always be stopped, inspected, and single-stepped. Compared to previous approaches, deoptimization allows more debugging while placing fewer restrictions on the optimizations that can be performed. • Polymorphic inline caching generates type-case sequences on-the-fly to speed up messages sent from the same call site to several different types of object. More significantly, they collect concrete type information for the optimizing compiler. With better performance yet good interactive behavior, these techniques make exploratory programming possible both for pure object-oriented languages and for application domains requiring higher ultimate performance, reconciling exploratory programming, ubiquitous abstraction, and high performance.

A technique for representing programs abstractly and independently of the eventual target architecture is presented that yields a file representation twice as compact as machine code for a CISC processor. It forms the basis of an implementation, in which the process of code generation is deferred until the time of loading. At that point, native code is created on_the_fly by a code_generating loader. The process of loading with dynamic code_generation is so fast that it requires little more time than the input of equivalent native code from a disk storage medium. This is predominantly due to the compactness of the abstract program representation, which allows to counterbalance the ad...

Software systems have been using “just-in-time ” compilation (JIT) techniques since the 1960s. Broadly, JIT compilation includes any translation performed dynamically, after a program has started execution. We examine the motivation behind JIT compilation and constraints imposed on JIT compilation systems, and present a classification scheme for

Virtual machines face significant performance challenges beyond those confronted by traditional static optimizers. First, portable program representations and dynamic language features, such as dynamic class loading, force the deferral of most optimizations until runtime, inducing runtime optimization overhead. Second, modular

. A machine_independent abstract program representation is presented that is twice as compact as machine code for a CISC processor. It forms the basis of an implementation, in which the process of code generation is deferred until the time of loading. Separate compilation of program modules with type_safe interfaces, and dynamic loading (with code generation) on a per_module basis are both supported. To users of the implemented system, working with modules in the abstract representation is as convenient as working with native object_files, although it leads to several new capabilities. The combination of portability with practicality denotes a step toward a software component industry. 1. Introduction The rapid evolution of hardware technology is constantly influencing software development, for better as well as for worse. On the downside, faster hardware can conceal the complexity and cost of badly_designed programs; Reiser [Rei89] is not far off the mark in observing that s...

Multi-core technology is being employed in most recent high-performance architectures. Such architectures need specifically designed multi-threaded software to exploit all the potentialities of their hardware parallelism. At the same time, object code virtualization technologies are achieving a growing popularity, as they allow higher levels of software portability and reuse. Thus, a virtual execution environment running on a multi-core processor has to run complex, high-level applications and to exploit as much as possible the underlying parallel hardware. We propose an approach that leverages on CMP features to expose a novel pipeline synchronization model for the internal threads of the dynamic compiler. Thanks to compilation latency masking effect of the pipeline organization, our dynamic compiler, ILDJIT, is able to achieve significant speedups (26 % on average) with respect to the baseline, when the underlying hardware exposes at least two cores.