Cooking the Books: Formalizing JMM Implementation Recipes

The Java Memory Model (JMM) is intended to characterize the meaning of concurrent Java programs. Because of the model\u27s complexity, however, its definition cannot be easily transplanted within an optimizing Java compiler, even though an important rationale for its design was to ensure Java compiler optimizations are not unduly hampered because of the language\u27s concurrency features. In response, Lea\u27s JSR-133 Cookbook for Compiler Writers, an informal guide to realizing the principles underlying the JMM on different (relaxed-memory) platforms was developed. The goal of the cookbook is to give compiler writers a relatively simple, yet reasonably efficient, set of reordering-based recipes that satisfy JMM constraints. In this paper, we present the first formalization of the cookbook, providing a semantic basis upon which the relationship between the recipes defined by the cookbook and the guarantees enforced by the JMM can be rigorously established. Notably, one artifact of our investigation is that the rules defined by the cookbook for compiling Java onto Power are inconsistent with the requirements of the JMM, a surprising result, and one which justifies our belief in the need for formally provable definitions to reason about sophisticated (and racy) concurrency patterns in Java, and their implementation on modern-day relaxed-memory hardware. Our formalization enables simulation arguments between an architecture-independent intermediate representation of the kind suggested by Lea with machine abstractions for Power and x86. Moreover, we provide fixes for cookbook recipes that are inconsistent with the behaviors admitted by the target platform, and prove the correctness of these repairs

Virtual Machine Support for Many-Core Architectures: Decoupling Abstract from Concrete Concurrency Models

The upcoming many-core architectures require software developers to exploit concurrency to utilize available computational power. Today's high-level language virtual machines (VMs), which are a cornerstone of software development, do not provide sufficient abstraction for concurrency concepts. We analyze concrete and abstract concurrency models and identify the challenges they impose for VMs. To provide sufficient concurrency support in VMs, we propose to integrate concurrency operations into VM instruction sets. Since there will always be VMs optimized for special purposes, our goal is to develop a methodology to design instruction sets with concurrency support. Therefore, we also propose a list of trade-offs that have to be investigated to advise the design of such instruction sets. As a first experiment, we implemented one instruction set extension for shared memory and one for non-shared memory concurrency. From our experimental results, we derived a list of requirements for a full-grown experimental environment for further research

Performance comparison between Java and JNI for optimal implementation of computational micro-kernels

General purpose CPUs used in high performance computing (HPC) support a vector instruction set and an out-of-order engine dedicated to increase the instruction level parallelism. Hence, related optimizations are currently critical to improve the performance of applications requiring numerical computation. Moreover, the use of a Java run-time environment such as the HotSpot Java Virtual Machine (JVM) in high performance computing is a promising alternative. It benefits from its programming flexibility, productivity and the performance is ensured by the Just-In-Time (JIT) compiler. Though, the JIT compiler suffers from two main drawbacks. First, the JIT is a black box for developers. We have no control over the generated code nor any feedback from its optimization phases like vectorization. Secondly, the time constraint narrows down the degree of optimization compared to static compilers like GCC or LLVM. So, it is compelling to use statically compiled code since it benefits from additional optimization reducing performance bottlenecks. Java enables to call native code from dynamic libraries through the Java Native Interface (JNI). Nevertheless, JNI methods are not inlined and require an additional cost to be invoked compared to Java ones. Therefore, to benefit from better static optimization, this call overhead must be leveraged by the amount of computation performed at each JNI invocation. In this paper we tackle this problem and we propose to do this analysis for a set of micro-kernels. Our goal is to select the most efficient implementation considering the amount of computation defined by the calling context. We also investigate the impact on performance of several different optimization schemes which are vectorization, out-of-order optimization, data alignment, method inlining and the use of native memory for JNI methods.Comment: Part of ADAPT Workshop proceedings, 2015 (arXiv:1412.2347

A compiler extension for parallelizing arrays automatically on the cell heterogeneous processor

This paper describes the approaches taken to extend an array programming language compiler using a Virtual SIMD Machine (VSM) model for parallelizing array operations on Cell Broadband Engine heterogeneous machine. This development is part of ongoing work at the University of Glasgow for developing array compilers that are beneficial for applications in many areas such as graphics, multimedia, image processing and scientific computation. Our extended compiler, which is built upon the VSM interface, eases the parallelization processes by allowing automatic parallelisation without the need for any annotations or process directives. The preliminary results demonstrate significant improvement especially on data-intensive applications

StreamJIT: A Commensal Compiler for High-Performance Stream Programming

There are many domain libraries, but despite the performance benefits of compilation, domain-specific languages are comparatively rare due to the high cost of implementing an optimizing compiler. We propose commensal compilation, a new strategy for compiling embedded domain-specific languages by reusing the massive investment in modern language virtual machine platforms. Commensal compilers use the host language's front-end, use host platform APIs that enable back-end optimizations by the host platform JIT, and use an autotuner for optimization selection. The cost of implementing a commensal compiler is only the cost of implementing the domain-specific optimizations. We demonstrate the concept by implementing a commensal compiler for the stream programming language StreamJIT atop the Java platform. Our compiler achieves performance 2.8 times better than the StreamIt native code (via GCC) compiler with considerably less implementation effort.United States. Dept. of Energy. Office of Science (X-Stack Award DE-SC0008923)Intel Corporation (Science and Technology Center for Big Data)SMART3 Graduate Fellowshi

Empowering Collections with Swarm Behavior

Often, when modelling a system there are properties and operations that are related to a group of objects rather than to a single object. In this paper we extend Java with Swarm Behavior, a new composition operator that associates behavior with a collection of instances. The lookup resolution of swarm behavior is based on the element type of a collection and is thus orthogonal to the collection hierarchy