J. Eliot B. Moss

The DaCapo benchmarks: java benchmarking development and analysis

Since benchmarks drive computer science research and industry product development, which ones we use and how we evaluate them are key questions for the community. Despite complex runtime tradeoffs due to dynamic compilation and garbage collection required for Java programs, many evaluations still use methodologies developed for C, C++, and Fortran. SPEC, the dominant purveyor of benchmarks, compounded this problem by institutionalizing these methodologies for their Java benchmark suite. This paper recommends benchmarking selection and evaluation methodologies, and introduces the DaCapo benchmarks, a set of open source, client-side Java benchmarks. We demonstrate that the complex interactions of (1) architecture, (2) compiler, (3) virtual machine, (4) memory management, and (5) application require more extensive evaluation than C, C++, and Fortran which stress (4) much less, and do not require (3). We use and introduce new value, time-series, and statistical metrics for static and dynamic properties such as code complexity, code size, heap composition, and pointer mutations. No benchmark suite is definitive, but these metrics show that DaCapo improves over SPEC Java in a variety of ways, including more complex code, richer object behaviors, and more demanding memory system requirements. This paper takes a step towards improving methodologies for choosing and evaluating benchmarks to foster innovation in system design and implementation for Java and other managed languages.

Open nesting in software transactional memory

Transactional memory (TM) promises to simplify concurrent programming while providing scalability competitive to fine-grained locking. Language-based constructs allow programmers to denote atomic regions declaratively and to rely on the underlying system to provide transactional guarantees along with concurrency. In contrast with fine-grained locking, TM allows programmers to write simpler programs that are composable and deadlock-free. TM implementations operate by tracking loads and stores to memory and by detecting concurrent conflicting accesses by different transactions. By automating this process, they greatly reduce the programmers burden, but they also are forced to be conservative. Incertain cases, conflicting memory accesses may not actually violate the higher-level semantics of a program, and a programmer may wish to allow seemingly conflicting transactions to execute concurrently. Open nested transactions enable expert programmers to differentiate between physical conflicts, at the level of memory, and logical conflicts that actually violate application semantics. A TMsystem with open nesting can permit physical conflicts that are not logical conflicts, and thus increase concurrency among application threads. Here we present an implementation of open nested transactions in a Java-based software transactional memory (STM)system. We describe new language constructs to support open nesting in Java, and we discuss new abstract locking mechanisms that a programmer can use to prevent logical conflicts. We demonstrate how these constructs can be mapped efficiently to existing STM data structures. Finally, we evaluate our system on a set of Java applications and data structures, demonstrating how open nesting can enhance application scalability.

Incremental Collection of Mature Objects

We present a garbage collection algorithm that extends generational scavenging to collect large older generations (mature objects) non-disruptively. The algorithms approach is to process bounded-size pieces of mature object space at each collection; the subtleties lie in guaranteeing that it eventually collects any and all garbage. The algorithm does not assume any special hardware or operating system support, e.g., for forwarding pointers or protection traps. The algorithm copies objects, so it naturally supports compaction and reclustering.

A comparative performance evaluation of write barrier implementation

Generational garbage collectors are able to achieve very small pause times by concentrating on the youngest (most recently allocated) objects when collecting, since objects have been observed to die young in many systems. Generational collectors must keep track of all pointers from older to younger generations, by “monitoring” all stores into the heap. This write barrier has been implemented in a number of ways, varying essentially in the granularity of the information observed and stored. Here we examine a range of write barrier implementations and evaluate their relative performance within a generation scavenging garbage collector for Smalltalk.

Type-based alias analysis

This paper evaluates three alias analyses based on programming language types. The first analysis uses type compatibility to determine aliases. The second extends the first by using additional high-level information such as field names. The third extends the second with a flow-insensitive analysis. Although other researchers suggests using types to disambiguate memory references, none evaluates its effectiveness. We perform both static and dynamic evaluations of type-based alias analyses for Modula-3, a statically-typed type-safe language. The static analysis reveals that type compatibility alone yields a very imprecise alias analysis, but the other two analyses significantly improve alias precision. We use redundant load elimination (RLE) to demonstrate the effectiveness of the three alias algorithms in terms of the opportunities for optimization, the impact on simulated execution times, and to compute an upper bound on what a perfect alias analysis would yield. We show modest dynamic improvements for (RLE), and more surprisingly, that on average our alias analysis is within 2.5% of a perfect alias analysis with respect to RLE on 8 Modula-3 programs. These results illustrate that to explore thoroughly the effectiveness of alias analyses, researchers need static, dynamic, and upper-bound analysis. In addition, we show that for type-safe languages like Modula-3 and Java, a fast and simple alias analysis may be sufficient for many applications.

The garbage collection advantage: improving program locality

As improvements in processor speed continue to outpace improvements in cache and memory speed, poor locality increasingly degrades performance. Because copying garbage collectors move objects, they have an opportunity to improve locality. However, no static copying order is guaranteed to match program traversal orders. This paper introduces <i>online object reordering</i> (OOR) which includes a new dynamic, online class analysis for Java that detects program traversal patterns and exploits them in a copying collector. OOR uses run-time method sampling that drives just-in-time (JIT) compilation. For each <i>hot</i> (frequently executed) method, OOR analysis identifies the hot field accesses. At garbage collection time, the OOR collector then copies referents of hot fields together with their parent. Enhancements include static analysis to exclude accesses in cold basic blocks, heuristics that decay heat to respond to phase changes, and a separate space for hot objects. The overhead of OOR is on average negligible and always less than 2% on Java benchmarks in Jikes RVM with MMTk. We compare program performance of OOR to static class-oblivious copying orders (e.g., breadth and depth first). Performance variation due to static orders is often low, but can be up to 25%. In contrast, OOR matches or improves upon the best static order since its history-based copying tunes memory layout to program traversal.

Design of the Mneme persistent object store

The Mneme project is an investigation of techniques for integrating programming language and database features to provide better support for cooperative, information-intensive tasks such as computer-aided software engineering. The project strategy is to implement efficient, distributed, persistent programming languages. We report here on the Mneme persistent object store, a fundamental component of the project, discussing its design and initial prototype. Mneme stores objects in a simple and general format, preserving object identity and object interrelationships. Specific goals for the store include portability, extensibility (especially with respect to object management policies), and performance. The model of memory that the store aims at is a single, cooperatively-shared heap, distributed across a collection of networked computers. The initial prototype is intended mainly to explore performance issues and to support object-oriented persistent programming languages. We include performance measurements from the prototype as well as more qualitative results.

Nested transactional memory: model and architecture sketches

We offer a reference model for nested transactions at the level of memory accesses, and sketch possible hardware architecture designs that implement that model. We describe both closed and open nesting. The model is abstract in that it does not relate to hardware, such as caches, but describes memory as seen by each transaction, memory access conflicts, and the effects of commits and aborts. The hardware sketches describe approaches to implementing the model using bounded size caches in a processor with overflows to memory. In addition to a model that will support concurrency within a transaction, we describe a simpler model that we call linear nesting. Linear nesting supports only a single thread of execution in a transaction nest, but may be easier to implement. While we hope that the model is a good target to which to compile transactions from source languages, the mapping from source constructs to nested transactional memory is beyond the scope of the paper.

Beltway: getting around garbage collection gridlock

We present the design and implementation of a new garbage collection framework that significantly generalizes existing copying collectors. The Beltway framework exploits and separates object age and incrementality. It groups objects in one or more increments on queues called belts, collects belts independently, and collects increments on a belt in first-in-first-out order. We show that Beltway configurations, selected by command line options, act and perform the same as semi-space, generational, and older-first collectors, and encompass all previous copying collectors of which we are aware. The increasing reliance on garbage collected languages such as Java requires that the collector perform well. We show that the generality of Beltway enables us to design and implement new collectors that are robust to variations in heap size and improve total execution time over the best generational copying collectors of which we are aware by up to 40%, and on average by 5 to 10%, for small to moderate heap sizes. New garbage collection algorithms are rare, and yet we define not just one, but a new family of collectors that subsumes previous work. This generality enables us to explore a larger design space and build better collectors.

Compiler support for garbage collection in a statically typed language

We consider the problem of supporting compacting garbage collection in the presence of modern compiler optimizations. Since our collector may move any heap object, it must accurately locate, follow, and update all pointers and values derived from pointers. To assist the collector, we extend the compiler to emit tables describing live pointers, and values derived from pointers, at each program location where collection may occur. Significant results include identification of a number of problems posed by optimizations, solutions to those problems, a working compiler, and experimental data concerning table sizes, table compression, and time overhead of decoding tables during collection. While gc support can affect the code produced, our sample programs show no significant changes, the table sizes are a modest fraction of the size of the optimized code, and stack tracing is a small fraction of total gc time. Since the compiler enhancements are also modest, we conclude that the approach is practical.