37 research outputs found

    Reducing the burden of parallel loop schedulers for many-core processors

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    Funder: FP7 People: Marie‐Curie Actions; Id: http://dx.doi.org/10.13039/100011264; Grant(s): 327744Summary: As core counts in processors increases, it becomes harder to schedule and distribute work in a timely and scalable manner. This article enhances the scalability of parallel loop schedulers by specializing schedulers for fine‐grain loops. We propose a low‐overhead work distribution mechanism for a static scheduler that uses no atomic operations. We integrate our static scheduler with the Intel OpenMP and Cilkplus parallel task schedulers to build hybrid schedulers. Compiler support enables efficient reductions for Cilk, without changing the programming interface of Cilk reducers. Detailed, quantitative measurements demonstrate that our techniques achieve scalable performance on a 48‐core machine and the scheduling overhead is 43% lower than Intel OpenMP and 12.1× lower than Cilk. We demonstrate consistent performance improvements on a range of HPC and data analytics codes. Performance gains are more important as loops become finer‐grain and thread counts increase. We observe consistently 16%–30% speedup on 48 threads, with a peak of 2.8× speedup

    Parallel Programming of General-Purpose Programs Using Task-Based Programming Models

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    The prevalence of multicore processors is bound to drive most kinds of software development towards parallel programming. To limit the difficulty and overhead of parallel software design and maintenance, it is crucial that parallel programming models allow an easy-to-understand, concise and dense representation of parallelism. Parallel programming models such as Cilk++ and Intel TBBs attempt to offer a better, higher-level abstraction for parallel programming than threads and locking synchronization. It is not straightforward, however, to express all patterns of parallelism in these models. Pipelines are an important parallel construct, although difficult to express in Cilk and TBBs in a straightfor- ward way, not without a verbose restructuring of the code. In this paper we demonstrate that pipeline parallelism can be easily and concisely expressed in a Cilk-like language, which we extend with input, output and input/output dependency types on procedure arguments, enforced at runtime by the scheduler. We evaluate our implementation on real applications and show that our Cilk-like scheduler, extended to track and enforce these dependencies has performance comparable to Cilk++

    Memory abstractions for parallel programming

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 156-163).A memory abstraction is an abstraction layer between the program execution and the memory that provides a different "view" of a memory location depending on the execution context in which the memory access is made. Properly designed memory abstractions help ease the task of parallel programming by mitigating the complexity of synchronization or admitting more efficient use of resources. This dissertation describes five memory abstractions for parallel programming: (i) cactus stacks that interoperate with linear stacks, (ii) efficient reducers, (iii) reducer arrays, (iv) ownershipaware transactions, and (v) location-based memory fences. To demonstrate the utility of memory abstractions, my collaborators and I developed Cilk-M, a dynamically multithreaded concurrency platform which embodies the first three memory abstractions. Many dynamic multithreaded concurrency platforms incorporate cactus stacks to support multiple stack views for all the active children simultaneously. The use of cactus stacks, albeit essential, forces concurrency platforms to trade off between performance, memory consumption, and interoperability with serial code due to its incompatibility with linear stacks. This dissertation proposes a new strategy to build a cactus stack using thread-local memory mapping (or TLMM), which enables Cilk-M to satisfy all three criteria simultaneously. A reducer hyperobject allows different branches of a dynamic multithreaded program to maintain coordinated local views of the same nonlocal variable. With reducers, one can use nonlocal variables in a parallel computation without restructuring the code or introducing races. This dissertation introduces memory-mapped reducers, which admits a much more efficient access compared to existing implementations. When used in large quantity, reducers incur unnecessarily high overhead in execution time and space consumption. This dissertation describes support for reducer arrays, which offers the same functionality as an array of reducers with significantly less overhead. Transactional memory is a high-level synchronization mechanism, designed to be easier to use and more composable than fine-grain locking. This dissertation presents ownership-aware transactions, the first transactional memory design that provides provable safety guarantees for "opennested" transactions. On architectures that implement memory models weaker than sequential consistency, programs communicating via shared memory must employ memory-fences to ensure correct execution. This dissertation examines the concept of location-based memoryfences, which unlike traditional memory fences, incurs latency only when synchronization is necessary.by I-Ting Angelina Lee.Ph.D

    The Cilkview scalability analyzer

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    The Cilkview scalability analyzer is a software tool for profiling, estimating scalability, and benchmarking multithreaded Cilk++ ap-plications. Cilkview monitors logical parallelism during an instru-mented execution of the Cilk++ application on a single process-ing core. As Cilkview executes, it analyzes logical dependencies within the computation to determine its work and span (critical-path length). These metrics allow Cilkview to estimate parallelism and predict how the application will scale with the number of pro-cessing cores. In addition, Cilkview analyzes scheduling overhead using the concept of a “burdened dag, ” which allows it to diagnose performance problems in the application due to an insufficient grain size of parallel subcomputations. Cilkview employs the Pin dynamic-instrumentation framework to collect metrics during a serial execution of the application code. It operates directly on the optimized code rather than on a debug version. Metadata embedded by the Cilk++ compiler in the binary executable identifies the parallel control constructs in the executing application. This approach introduces little or no overhead to the program binary in normal runs. Cilkview can perform real-time scalability benchmarking auto-matically, producing gnuplot-compatible output that allows devel-opers to compare an application’s performance with the tool’s pre-dictions. If the program performs beneath the range of expectation, the programmer can be confident in seeking a cause such as insuf-ficient memory bandwidth, false sharing, or contention, rather than inadequate parallelism or insufficient grain size

    Exploiting commutativity to reduce the cost of updates to shared data in cache-coherent systems

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    We present Coup, a technique to lower the cost of updates to shared data in cache-coherent systems. Coup exploits the insight that many update operations, such as additions and bitwise logical operations, are commutative: they produce the same final result regardless of the order they are performed in. Coup allows multiple private caches to simultaneously hold update-only permission to the same cache line. Caches with update-only permission can locally buffer and coalesce updates to the line, but cannot satisfy read requests. Upon a read request, Coup reduces the partial updates buffered in private caches to produce the final value. Coup integrates seamlessly into existing coherence protocols, requires inexpensive hardware, and does not affect the memory consistency model. We apply Coup to speed up single-word updates to shared data. On a simulated 128-core, 8-socket system, Coup accelerates state-of-the-art implementations of update-heavy algorithms by up to 2.4×.Center for Future Architectures ResearchNational Science Foundation (U.S.) (CAREER-1452994)Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Grier Presidential Fellowship)Microelectronics Advanced Research CorporationUnited States. Defense Advanced Research Projects Agenc

    Efficient and Reasonable Object-Oriented Concurrency

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    Making threaded programs safe and easy to reason about is one of the chief difficulties in modern programming. This work provides an efficient execution model for SCOOP, a concurrency approach that provides not only data race freedom but also pre/postcondition reasoning guarantees between threads. The extensions we propose influence both the underlying semantics to increase the amount of concurrent execution that is possible, exclude certain classes of deadlocks, and enable greater performance. These extensions are used as the basis an efficient runtime and optimization pass that improve performance 15x over a baseline implementation. This new implementation of SCOOP is also 2x faster than other well-known safe concurrent languages. The measurements are based on both coordination-intensive and data-manipulation-intensive benchmarks designed to offer a mixture of workloads.Comment: Proceedings of the 10th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE '15). ACM, 201
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