A performance model for X10 applications

Grove, David; Tardieu, Olivier; Cunningham, David; Herta, Ben; Peshansky, Igor; Saraswat, Vijay

doi:10.1145/2212736.2212737

Cited by 28 publications

(27 citation statements)

References 8 publications

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“…For example, receiver-initiated algorithms may be not as well suited to multiprogrammed environments because an idle processor takes exclusive access to a specific victim, which can delay execution if the sender is swapped out. Also, in receiver-initiated systems, processors can spin while looking for work, thereby making it difficult for the job scheduler to identify idle processors [22]. In contrast, in the sender-initiated approach, any sender can send work to an idle processor, and idle processors do not spin to look for work.…”

Section: Related Workmentioning

confidence: 99%

Scheduling parallel programs by work stealing with private deques

2013

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Work stealing has proven to be an effective method for scheduling fine-grained parallel programs on multicore computers. To achieve high performance, work stealing distributes tasks between concurrent queues, called deques, assigned to each processor. Each processor operates on its deque locally except when performing load balancing via steals. Unfortunately, concurrent deques suffer from two limitations: 1) local deque operations require expensive memory fences in modern weak-memory architectures, 2) they can be very difficult to extend to support various optimizations and flexible forms of task distribution strategies needed many applications, e.g., those that do not fit nicely into the divide-and-conquer, nested data parallel paradigm.For these reasons, there has been a lot recent interest in implementations of work stealing with non-concurrent deques, where deques remain entirely private to each processor and load balancing is performed via message passing. Private deques eliminate the need for memory fences from local operations and enable the design and implementation of efficient techniques for reducing task-creation overheads and improving task distribution. These advantages, however, come at the cost of communication. It is not known whether work stealing with private deques enjoys the theoretical guarantees of concurrent deques and whether they can be effective in practice.In this paper, we propose two work-stealing algorithms with private deques and prove that the algorithms guarantee similar theoretical bounds as work stealing with concurrent deques. For the analysis, we use a probabilistic model and consider a new parameter, the branching depth of the computation. We present an implementation of the algorithm as a C++ library and show that it compares well to Cilk on a range of benchmarks. Since our approach relies on private deques, it enables implementing flexible task creation and distribution strategies. As a specific example, we show how to implement task coalescing and steal-half strategies, which can be important in fine-grain, non-divide-and-conquer algorithms such as graph algorithms, and apply them to the depth-first-search problem.

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Section: Related Workmentioning

confidence: 99%

Scheduling parallel programs by work stealing with private deques

2013

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“…In X10, a place represents a distinct computational node with a distinct scheduler [14]. In accordance with this model, we assume that scheduling decisions are made on a per-place basis, and the choice of which activity to run at a given place depends only on the set of activities currently executing at that place.…”

Section: Schedulingmentioning

confidence: 99%

“…Scheduling algorithms that depend on the history of computation at a place (such as the work-stealing scheduling algorithm used in the X10 runtime [14,15]) cannot be directly represented in this model. However, we believe the security guarantees still hold for the X10 runtime; we further discuss the security of the X10 scheduler in Section 4.…”

Section: Idleplacementioning

confidence: 99%

“…(It is correctly rejected by our security analysis.) In this example, Activity 1 moves to place High in order to perform computation on high-security data, before returning to place Low to perform the output of the string ''pos' '. We assume that the scheduling of activities at each place depends only on the activities at that place, an assumption that holds in the X10 2.2 runtime [14]. Nonetheless, in Program 2, the scheduling of Activity 2 at place Low depends on whether Activity 1 is running at Low, which in turn depends on how long the computation at place High takes.…”

Section: Introductionmentioning

confidence: 99%

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Towards a practical secure concurrent language

Muller

Chong

2012

SIGPLAN Not.

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We demonstrate that a practical concurrent language can be extended in a natural way with information security mechanisms that provably enforce strong information security guarantees. We extend the X10 concurrent programming language with coarse-grained information-flow control. Central to X10 concurrency abstractions is the notion of a place: a container for data and computation. We associate a security level with each place, and restrict each place to store only data appropriate for that security level. When places interact only with other places at the same security level, then our security mechanisms impose no restrictions. When places of differing security levels interact, our information security analysis prevents potentially dangerous information flows, including information flow through covert scheduling channels. The X10 concurrency mechanisms simplify reasoning about information flow in concurrent programs.We present a static analysis that enforces a noninterference-based extensional information security condition in a calculus that captures the key aspects of X10's place abstraction and async-finish parallelism. We extend this security analysis to support many of X10's language features, and have implemented a prototype compiler for the resulting language.

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“…And global synchronous operations are executed locally. The use of finish will induce some scheduling overheads, but relevant optimistic mechanisms have been established in the X10 scheduler [10].…”

Section: X10mentioning

confidence: 99%

Characterization of Smith-Waterman sequence database search in X10

Liu

Yang

2012

Proceedings of the 2012 ACM SIGPLAN X10 Workshop

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Productivity and performance are always viewed as two sides of parallel programming languages. X10 is a new object-oriented parallel language for both high-productivity and high-performance. To help the development of X10, we characterize the performance of X10 in bioinformatics using the fundamental application SmithWaterman (SW) sequence database search. We implement the SW application in X10 on multi-core shared-memory architecture. Through comparing with three SW implementations in C++, we make following suggestions for X10 as well as its compiler.(1) X10 compiler should improve its array access implementation in kernel loop to avoid redundant check and inefficient offset computation. The array access of the latest version X10 is much slower than that of C++, which results in poor singlecore performance of SW in X10.(2) X10 should support the utilization of SIMD instructions. With 128-bit SSE instructions, SW in X10 can achieve 8.7-17.7 fold speedup. Note that there are many applications in the world which can dramatically benefit from SIMD architectures on modern processors.

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A performance model for X10 applications

Cited by 28 publications

References 8 publications

Scheduling parallel programs by work stealing with private deques

Scheduling parallel programs by work stealing with private deques

Towards a practical secure concurrent language

Characterization of Smith-Waterman sequence database search in X10

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