Using Contaminated Garbage Collection and Reference Counting Garbage Collection to Provide Automatic Storage Reclamation for Real-Time Systems

Language support of dynamic storage management simplifies the application programming task immensely. As a result, dynamic storage allocation and garbage collection have become common in general purpose computing. Garbage collection research has led to the development of algorithms for locating program memory that is no longer in use and returning the unused memory to the run-time system for late use by the program. While many programming languages have adopted automatic memory reclamation features, this has not been the trend in Real-Time systems. Many garbage collection methods involve some form of marking the objects in memory. This marking requires time proportional to the size of the head to complete. As a result, the predictability constraints of Real-Time are often not satisfied by such approaches. In this thesis, we present an analysis of several approaches for program garbage collection. We examine two approximate collection strategies (Reference Counting and Contamination Garbage Collection) and one complete collection approach (Mark and Sweep Garbage Collection). Additionally, we analyze the relative success of each approach for meeting the demands of Real-Time computing. In addition, we present an algorithm that attempts to classify object types as good candidates for reference counting. Our approach is conservative and uses static analysis of an application\u27s type system. Our analysis of these three collection strategies leads to the observation that there could be benefits to using multiple garbage collectors in parallel. Consequently we address challenges associated with using multiple garbage collectors in one application

Static Determination of Allocation Rates to Support Real-Time Garbage Collection

While it is generally accepted that garbage-collected languages offer advantages over languages in which objects must be explicitly deallocated, real-time developers are leery of the adverse effects a garbage collector might have on real-time performance. Semiautomatic approaches based on regions have been proposed, but incorrect usage could cause unbounded storage leaks or program failure. Moreover, correct usage cannot be guaranteed at compile-time. Recently, real-time garbage collectors have been developed that provide a guaranteed fraction of the CPU to the application, and the correct operation of those collectors has been proven, subject only to the specification of certain statistics related to the type and rate of objects allocated by the application. However, unless those statistics are provided or estimated appropriately, the collector may fail to collect dead storage at a rate sufficient to pace the application’s need. Overspecification of those statistics is safe, but leaves the application with less than its possible share of the CPU, which may prevent the application from meeting its deadlines. In this thesis, we present a dynamic and static analysis of one such statistic, namely the real-time application’s memory allocation rate. The dynamic analysis highlights the variability of a program’s allocation rate. It also serves to quantify the conservatism of the statically computed upper bound. The static analysis is based on a data flow framework that requires interprocedural evaluation. We present the framework and results from analyzing some Java benchmarks from the jvm98 suite. Our work is a necessary step toward making real-time garbage collectors attractive to the hard-real-time community. By guaranteeing a bound on statistics provided to a real-time collector, we can guarantee the operation of the collector for a given application

Precise garbage collection for C

Journal ArticleMagpie is a source-to-source transformation for C programs that enables precise garbage collection, where precise means that integers are not confused with pointers, and the liveness of a pointer is apparent at the source level. Precise GC is primarily useful for long-running programs and programs that interact with untrusted components. In particular, we have successfully deployed precise GC in the C implementation of a language run-time system that was originally designed to use conservative GC. We also report on our experience in transforming parts of the Linux kernel to use precise GC instead of manual memory management

High-level real-time programming in Java

Real-time systems have reached a level of complexity beyond the scaling capability of the low-level or restricted languages traditionally used for real-time programming. While Metronome garbage collection has made it practical to use Java to implement real-time systems, many challenges remain for the construction of complex real-time systems, some specic to the use of Java and others simply due to the change in scale of such systems. The goal of our research is the creation of a comprehensive Java-based programming environment and methodology for the creation of complex real-time systems. Our goals include construction of a provably correct real-time garbage collec-tor capable of providing worst case latencies of 100 s, capa-ble of scaling from sensor nodes up to large multiprocessors; specialized programming constructs that retain the safety and simplicity of Java, and yet provide sub-microsecond la-tencies; the extension of Java's \write once, run anywhere" principle from functional correctness to timing behavior; on-line analysis and visualization that aids in the understanding of complex behaviors; and a principled probabilistic analy-sis methodology for bounding the behavior of the resulting systems. While much remains to be done, this paper describes the progress we have made towards these goals

Subheap-Augmented Garbage Collection

Automated memory management avoids the tedium and danger of manual techniques. However, as no programmer input is required, no widely available interface exists to permit principled control over sometimes unacceptable performance costs. This dissertation explores the idea that performance-oriented languages should give programmers greater control over where and when the garbage collector (GC) expends effort. We describe an interface and implementation to expose heap partitioning and collection decisions without compromising type safety. We show that our interface allows the programmer to encode a form of reference counting using Hayes\u27 notion of key objects. Preliminary experimental data suggests that our proposed mechanism can avoid high overheads suffered by tracing collectors in some scenarios, especially with tight heaps. However, for other applications, the costs of applying subheaps---in human effort and runtime overheads---remain daunting

An efficient implementation of lazy functional programming languages based on the generalized intensional transformation

Αυτή η εργασία διερευνά θεωρητικά και πρακτικά ζητήματα της αλληλεπίδρασης μεταξύ (ευρέως γνωστών και νέων) τεχνικών μεταγλώττισης, όπως ο γενικευμένος νοηματικός μετασχηματισμός, ο μετασχηματισμός σε συναρτησιακά αντικείμενα, η ξεχωριστή μεταγλώττιση και η λάμβδα άρση. Ένας πειραματικός μεταγλωττιστής για τη γλώσσα Haskell (GIC), ο οποίος χρησιμοποιεί τις τεχνικές αυτές, δίνει τη δυνατότητα σε νέες ιδέες να υλοποιηθούν και να αξιολογηθούν μέσα σε ένα πρακτικό πλαίσιο. Ως μέρος αυτής της δουλειάς πραγματοποιήθηκαν διάφορες προσθήκες και αλλαγές στο μεταγλωττιστή, είτε προκειμένου να γίνει ο μεταγλωττιστής πληρέστερος είτε προκειμένου να βελτιωθεί ο τελικός κώδικας που παράγεται από το LAR back-end του μεταγλωττιστή.This dissertation investigates theoretical and practical issues of the integration between (well-known and novel) compilation techniques, such as the generalized intensional transformation, defunctionalization, separate compilation, and lambda lifting. An experimental Haskell compiler (GIC), which incorporates these techniques, serves as a workbench allowing ideas to be demonstrated and evaluated in a practical context. Within the scope of this work, several additions and changes were made to the compiler either towards enchancing the tool’s robustness or towards the optimization of the code generated by the compiler’s LAR back-end