Thread scheduling for multiprogrammed multiprocessors

Arora, Neha; Blumofe, Robert D.; Plaxton, C. Greg

doi:10.1145/277651.277678

Cited by 252 publications

(98 citation statements)

References 34 publications

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“…The tree formed over all nodes with enable edges is referred to as enabling tree [13]. depth(u) denotes the distance of node u from the root in the enabling tree.…”

Section: Useful Notationsmentioning

confidence: 99%

“…We leverage the proof methodology first proposed in [13] for pure work stealing based scheduling in a single SMP node. Our unique contributions are (a) proof that prioritized random inter-place work stealing is efficient using suitable probability density function, and, (b) proof of the lower and upper bounds of time complexity and message complexity for the multi-place distributed scheduling algorithm presented in Section 3.1.…”

Section: Time Complexity Analysismentioning

confidence: 99%

“…We compute the bound on the number of tokens in the ready-node-throw bucket and remote-place-throw bucket using potential function based analysis [13]. Let there be a non-negative potential with ready nodes (each representing one instruction) in a computation DAG.…”

Section: Lemmamentioning

confidence: 99%

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Performance driven distributed scheduling of parallel hybrid computations

Narang

Shyamasundar

2011

Theoretical Computer Science

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a b s t r a c tExascale computing is fast becoming a mainstream research area. In order to realize exascale performance, it is necessary to have efficient scheduling of large parallel computations with scalable performance on a large number of cores/processors. The scheduler needs to execute in a pure distributed and online fashion, should follow affinity inherent in the computation and must have low time and message complexity. Further, it should also avoid physical deadlocks due to bounded resources including space/memory per core. Simultaneous consideration of these factors makes affinity driven distributed scheduling particularly challenging. We attempt to address this challenge for hybrid parallel computations which contain tasks that have pre-specified affinity to a place and also tasks that can be mapped to any place in the system. Specifically, we address two scheduling problems of the type P m |M j , prec|C max . This paper presents online distributed scheduling algorithms for hybrid parallel computations assuming both unconstrained and bounded space per place. We also present the time and message complexity for distributed scheduling of hybrid computations. To the best of our knowledge, this is the first time that distributed scheduling algorithms for hybrid parallel computations have been presented and analyzed for time and message bounds under both unconstrained space and bounded space.

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“…The tree formed over all nodes with enable edges is referred to as enabling tree [13]. depth(u) denotes the distance of node u from the root in the enabling tree.…”

Section: Useful Notationsmentioning

confidence: 99%

Section: Time Complexity Analysismentioning

confidence: 99%

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Performance driven distributed scheduling of parallel hybrid computations

Narang

Shyamasundar

2011

Theoretical Computer Science

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“…The reason is that between the decision and migration gap, the load view of the system might have changed. Inspired by the work stealing algorithm [23] used in MIMD-style parallel computer, we proposed a cooperated migration mechanism, which combines the virtue of work sharing and work stealing, and thinks heavily on cache effect on multi-processor system.…”

Section: Load Balance In Simkmentioning

confidence: 99%

“…So we redesign the mig list to use doubleended stack proposed by Arora [23] . In this mode, local threads enque and deque from bottom, and other threads deque from top.…”

Section: Load Balance In Simkmentioning

confidence: 99%

SimK: A Large-Scale Parallel Simulation Engine

Chen

Gong

et al. 2009

J. Comput. Sci. Technol.

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Simulation is an important method to evaluate future computer systems. Currently microprocessor architecture has switched to parallel, but almost all simulators remained at sequential stage, and the advantages brought by multi-core or many-core processors cannot be utilized. This paper presents a parallel simulator engine (SimK) towards the prevalent SMP/CMP platform, aiming at large-scale fine-grained computer system simulation. In this paper, highly efficient synchronization, communication and buffer management policies used in SimK are introduced, and a novel lock-free scheduling mechanism that avoids using any atomic instructions is presented. To deal with the load fluctuation at light load case, a cooperated dynamic task migration scheme is proposed. Based on SimK, we have developed large-scale parallel simulators HppSim and HppNetSim, which simulate a full supercomputer system and its interconnection network respectively. Results show that HppSim and HppNetSim both gain sound speedup with multiple processors, and the best normalized speedup reaches 14.95X on a two-way quad-core server.

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Adaptive demand‐aware work‐stealing in multi‐programmed multi‐core architectures

Chen

Zheng

Guo

2015

Concurrency and Computation

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SUMMARYModern multi-core computers often execute multiple programs concurrently, but traditional work-stealing schedulers assume that only a single program executes at a time. If multiple work-stealing programs run on a multi-core computer concurrently, the performance of these co-located programs is poor and unbalanced due to the interference among their workers. To relieve this problem, this paper proposes demand-aware work-stealing (DWS) for a single work-stealing program. If multiple programs that adopt DWS run simultaneously on a multi-core system, the computation resources are evenly allocated to the co-located programs at the beginning. At runtime, if a program does not need all its allocated cores, it donates its free cores. Otherwise, if a program needs more cores, it steals the free cores donated by its co-located programs. In addition, each program that adopts DWS dynamically puts its workers to sleep and wakes them up according to the number of its queued tasks. Experimental results show that DWS can improve the co-located programs' performance up to 42.6% and can also balance the performance of the co-located programs compared with traditional work-stealing.

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Thread scheduling for multiprogrammed multiprocessors

Abstract: We present a user-level thread scheduler for shared-memory mul-

Cited by 252 publications

References 34 publications

Performance driven distributed scheduling of parallel hybrid computations

Performance driven distributed scheduling of parallel hybrid computations

SimK: A Large-Scale Parallel Simulation Engine

Adaptive demand‐aware work‐stealing in multi‐programmed multi‐core architectures

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