Code generation for a multithreaded register sharing architecture is inherently complex and involves some issues absent in conventional code compilation. To approach the problem, we define a consistency contract between the program and the hardware and require the compiler to preserve the contract during code transformations. To apply the contract to compiler implementation, we develop a correctness framework that ensures preservation of the contract and use it to adjust the code optimizations for correctness under parallel code. One area that is naturally affected by register sharing is register allocation. We discuss adaptation of existing coloring-based algorithms for shared code and show how they benefit from the consistency contract. Another benefit affects the general compiler optimizations. We show that these optimizations need very little restrictions in order to be correct for parallel code, allowing the compiler to realize its potential to a high degree.

We investigate extremely fine-grain multithreading as a means for improving energy efficiency of single-task program execution.Our work is based on low-overhead threads executing an explicitly parallel program in a register-sharing context. The thread-based parallelism takes the place of instruction-level parallelism, allowing us to use simple and more energy-efficient in-order pipelines while retaining performance that is characteristic of classical out-of-order processors. Our evaluation shows that in energy terms, the parallelized code running over in-order pipelines can outperform both plain in-order and out-of-order processors.

Performance of multithreaded programs is heavily influenced by the latencies of the thread management and synchronization operations. Improving these latencies becomes especially important when the parallelization is performed at fine granularity. In this work we examine the interaction of speculative execution with the thread-related operations. We develop a unified framework which allows all such operations to be executed speculatively and provides efficient recovery mechanisms to handle misspeculation of branches which affect instructions in several threads. The framework was evaluated in the context of Inthreads, a programming model designed for very fine grain parallelization. Our measurements show that the speedup obtained by speculative execution of the threads-related instructions can reach 25%.

The Java Language Specification (JLS) [Gosling et al. 1996] provides an operational definition for the consistency of shared variables. The definition remains unchanged in the JLS 2nd edition, currently under peer review, which relies on a specific abstract machine as its underlying model, is very complicated. Several subsequent works have tried to simplify and formalize it. However, these revised definitions are also operational, and thus have failed to highlight the intuition behind the original specification. In this work we provide a complete nonoperational specification for Java and for the JVM, excluding synchronized operations. We provide a simpler definition, in which we clearly distinguish the consistency model that is promised to the programmer from that which should be implemented in the JVM. This distinction, which was implicit in the original definition, is crucial for building the JVM. We find that the programmer model is strictly weaker than that of the JVM, and precisely define their discrepancy. Moreover, our definition is independent of any specific (or even abstract) machine, and can thus be used to verify JVM implementations and compiler optimizations on any platform. Finally, we show the precise range of consistency relaxations obtainable for the Java memory model when a certain compiler optimization— called prescient stores in JLS—is applicable.