8,113 research outputs found

    The Potential of Synergistic Static, Dynamic and Speculative Loop Nest Optimizations for Automatic Parallelization

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    Research in automatic parallelization of loop-centric programs started with static analysis, then broadened its arsenal to include dynamic inspection-execution and speculative execution, the best results involving hybrid static-dynamic schemes. Beyond the detection of parallelism in a sequential program, scalable parallelization on many-core processors involves hard and interesting parallelism adaptation and mapping challenges. These challenges include tailoring data locality to the memory hierarchy, structuring independent tasks hierarchically to exploit multiple levels of parallelism, tuning the synchronization grain, balancing the execution load, decoupling the execution into thread-level pipelines, and leveraging heterogeneous hardware with specialized accelerators. The polyhedral framework allows to model, construct and apply very complex loop nest transformations addressing most of the parallelism adaptation and mapping challenges. But apart from hardware-specific, back-end oriented transformations (if-conversion, trace scheduling, value prediction), loop nest optimization has essentially ignored dynamic and speculative techniques. Research in polyhedral compilation recently reached a significant milestone towards the support of dynamic, data-dependent control flow. This opens a large avenue for blending dynamic analyses and speculative techniques with advanced loop nest optimizations. Selecting real-world examples from SPEC benchmarks and numerical kernels, we make a case for the design of synergistic static, dynamic and speculative loop transformation techniques. We also sketch the embedding of dynamic information, including speculative assumptions, in the heart of affine transformation search spaces

    Factoring out ordered sections to expose thread-level parallelism

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    With the rise of multi-core processors, researchers are taking a new look at extending the applicability auto-parallelization techniques. In this paper, we identify a dependence pattern on which autoparallelization currently fails. This dependence pattern occurs for ordered sections, i.e. code fragments in a loop that must be executed atomically and in original program order. We discuss why these ordered sections prohibit current auto-parallelizers from working and we present a technique to deal with them. We experimentally demonstrate the efficacy of the technique, yielding significant overall program speedups

    A wide-spectrum language for verification of programs on weak memory models

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    Modern processors deploy a variety of weak memory models, which for efficiency reasons may (appear to) execute instructions in an order different to that specified by the program text. The consequences of instruction reordering can be complex and subtle, and can impact on ensuring correctness. Previous work on the semantics of weak memory models has focussed on the behaviour of assembler-level programs. In this paper we utilise that work to extract some general principles underlying instruction reordering, and apply those principles to a wide-spectrum language encompassing abstract data types as well as low-level assembler code. The goal is to support reasoning about implementations of data structures for modern processors with respect to an abstract specification. Specifically, we define an operational semantics, from which we derive some properties of program refinement, and encode the semantics in the rewriting engine Maude as a model-checking tool. The tool is used to validate the semantics against the behaviour of a set of litmus tests (small assembler programs) run on hardware, and also to model check implementations of data structures from the literature against their abstract specifications

    Putting Instruction Sequences into Effect

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    An attempt is made to define the concept of execution of an instruction sequence. It is found to be a special case of directly putting into effect of an instruction sequence. Directly putting into effect of an instruction sequences comprises interpretation as well as execution. Directly putting into effect is a special case of putting into effect with other special cases classified as indirectly putting into effect

    A Survey on Thread-Level Speculation Techniques

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    Producción CientíficaThread-Level Speculation (TLS) is a promising technique that allows the parallel execution of sequential code without relying on a prior, compile-time-dependence analysis. In this work, we introduce the technique, present a taxonomy of TLS solutions, and summarize and put into perspective the most relevant advances in this field.MICINN (Spain) and ERDF program of the European Union: HomProg-HetSys project (TIN2014-58876-P), CAPAP-H5 network (TIN2014-53522-REDT), and COST Program Action IC1305: Network for Sustainable Ultrascale Computing (NESUS)

    Synchronising C/C++ and POWER

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    Shared memory concurrency relies on synchronisation primitives: compare-and-swap, load-reserve/store-conditional (aka LL/SC), language-level mutexes, and so on. In a sequentially consistent setting, or even in the TSO setting of x86 and Sparc, these have well-understood semantics. But in the very relaxed settings of IBM®, POWER®, ARM, or C/C++, it remains surprisingly unclear exactly what the programmer can depend on. This paper studies relaxed-memory synchronisation. On the hardware side, we give a clear semantic characterisation of the load-reserve/store-conditional primitives as provided by POWER multiprocessors, for the first time since they were introduced 20 years ago; we cover their interaction with relaxed loads, stores, barriers, and dependencies. Our model, while not officially sanctioned by the vendor, is validated by extensive testing, comparing actual implementation behaviour against an oracle generated from the model, and by detailed discussion with IBM staff. We believe the ARM semantics to be similar. On the software side, we prove sound a proposed compilation scheme of the C/C++ synchronisation constructs to POWER, including C/C++ spinlock mutexes, fences, and read-modify-write operations, together with the simpler atomic operations for which soundness is already known from our previous work; this is a first step in verifying concurrent algorithms that use load-reserve/store-conditional with respect to a realistic semantics. We also build confidence in the C/C++ model in its own terms, fixing some omissions and contributing to the C standards committee adoption of the C++11 concurrency model

    Energy-efficient and high-performance lock speculation hardware for embedded multicore systems

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    Embedded systems are becoming increasingly common in everyday life and like their general-purpose counterparts, they have shifted towards shared memory multicore architectures. However, they are much more resource constrained, and as they often run on batteries, energy efficiency becomes critically important. In such systems, achieving high concurrency is a key demand for delivering satisfactory performance at low energy cost. In order to achieve this high concurrency, consistency across the shared memory hierarchy must be accomplished in a cost-effective manner in terms of performance, energy, and implementation complexity. In this article, we propose Embedded-Spec, a hardware solution for supporting transparent lock speculation, without the requirement for special supporting instructions. Using this approach, we evaluate the energy consumption and performance of a suite of benchmarks, exploring a range of contention management and retry policies. We conclude that for resource-constrained platforms, lock speculation can provide real benefits in terms of improved concurrency and energy efficiency, as long as the underlying hardware support is carefully configured.This work is supported in part by NSF under Grants CCF-0903384, CCF-0903295, CNS-1319495, and CNS-1319095 as well the Semiconductor Research Corporation under grant number 1983.001. (CCF-0903384 - NSF; CCF-0903295 - NSF; CNS-1319495 - NSF; CNS-1319095 - NSF; 1983.001 - Semiconductor Research Corporation
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