GNU epsilon - an extensible programming language

Reductionism is a viable strategy for designing and implementing practical programming languages, leading to solutions which are easier to extend, experiment with and formally analyze. We formally specify and implement an extensible programming language, based on a minimalistic first-order imperative core language plus strong abstraction mechanisms, reflection and self-modification features. The language can be extended to very high levels: by using Lisp-style macros and code-to-code transforms which automatically rewrite high-level expressions into core forms, we define closures and first-class continuations on top of the core. Non-self-modifying programs can be analyzed and formally reasoned upon, thanks to the language simple semantics. We formally develop a static analysis and prove a soundness property with respect to the dynamic semantics. We develop a parallel garbage collector suitable to multi-core machines to permit efficient execution of parallel programs.Comment: 172 pages, PhD thesi

Exploration of Dynamic Memory

Since the advent of the Java programming language and the development of real-time garbage collection, Java has become an option for implementing real-time applications. The memory management choices provided by real-time garbage collection allow for real-time eJava developers to spend more of their time implementing real-time solutions. Unfortunately, the real-time community is not convinced that real-time garbage collection works in managing memory for Java applications deployed in a real-time context. Consequently, the Real-Time for Java Expert Group formulated the Real-Time Specification for Java (RTSJ) standards to make Java a real-time programming language. In lieu of garbage collection, the RTSJ proposed a new memory model called scopes, and a new type of thread called NoHeapRealTimeThread (NHRT), which takes advantage of scopes. While scopes and NHRTs promise predictable allocation and deallocation behaviors, no asymptotic studies have been conducted to investigate the costs associated with these technologies. To understand the costs associated with using these technologies to manage memory, computations and analyses of time and space overheads associated with scopes and NHRTs are presented. These results provide a framework for comparing the RTSJ’s memory management model with real-time garbage collection. Another facet of this research concerns the optimization of novel approaches to garbage collection on multiprocessor systems. Such approaches yield features that are suitable for real-time systems. Although multiprocessor, concurrent garbage collection is not the same as real-time garbage collection, advancements in multiprocessor concurrent garbage collection have demonstrated the feasibility of building low latency multiprocessor real-time garbage collectors. In the nineteen-sixties, only three garbage collection schemes were available, namely reference counting garbage collection, mark-sweep garbage collection, and copying garbage collection. These classical approaches gave new insight into the discipline of memory management and inspired researchers to develop new, more elaborate memory-management techniques. Those insights resulted in a plethora of automatic memory management algorithms and techniques, and a lack of uniformity in the language used to reason about garbage collection. To bring a sense of uniformity to the language used to reason about garbage collection technologies, a taxonomy for comparing garbage collection technologies is presented

A software cache management system

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1985.MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERINGBibliography: leaves 49-50.by Jeffrey N. Eisen.M.S

Garbage collection in distributed systems

PhD ThesisThe provision of system-wide heap storage has a number of advantages. However, when the technique is applied to distributed systems automatically recovering inaccessible variables becomes a serious problem. This thesis presents a survey of such garbage collection techniques but finds that no existing algorithm is entirely suitable. A new, general purpose algorithm is developed and presented which allows individual systems to garbage collect largely independently. The effects of these garbage collections are combined, using recursively structured control mechanisms, to achieve garbage collection of the entire heap with the minimum of overheads. Experimental results show that new algorithm recovers most inaccessible variables more quickly than a straightforward garbage collection, giving an improved memory utilisation

The construction of high-performance virtual machines for dynamic languages

Dynamic languages, such as Python and Ruby, have become more widely used over the past decade. Despite this, the standard virtual machines for these languages have disappointing performance. These virtual machines are slow, not because methods for achieving better performance are unknown, but because their implementation is hard. What makes the implementation of high-performance virtual machines difficult is not that they are large pieces of software, but that there are fundamental and complex interdependencies between their components. In order to work together correctly, the interpreter, just-in-time compiler, garbage collector and library must all conform to the same precise low-level protocols. In this dissertation I describe a method for constructing virtual machines for dynamic languages, and explain how to design a virtual machine toolkit by building it around an abstract machine. The design and implementation of such a toolkit, the Glasgow Virtual Machine Toolkit, is described. The Glasgow Virtual Machine Toolkit automatically generates a just-in-time compiler, integrates precise garbage collection into the virtual machine, and automatically manages the complex inter-dependencies between all the virtual machine components. Two different virtual machines have been constructed using the GVMT. One is a minimal implementation of Scheme; which was implemented in under three weeks to demonstrate that toolkits like the GVMT can enable the easy construction of virtual machines. The second, the HotPy VM for Python, is a high-performance virtual machine; it demonstrates that a virtual machine built with a toolkit can be fast and that the use of a toolkit does not overly constrain the high-level design. Evaluation shows that HotPy outperforms the standard Python interpreter, CPython, by a large margin, and has performance on a par with PyPy, the fastest Python VM currently available