Journal ArticleDOI
Scheduling multithreaded computations by work stealing
TLDR
This paper gives the first provably good work-stealing scheduler for multithreaded computations with dependencies, and shows that the expected time to execute a fully strict computation on P processors using this scheduler is 1:1.Abstract:
This paper studies the problem of efficiently schedulling fully strict (i.e., well-structured) multithreaded computations on parallel computers. A popular and practical method of scheduling this kind of dynamic MIMD-style computation is “work stealing,” in which processors needing work steal computational threads from other processors. In this paper, we give the first provably good work-stealing scheduler for multithreaded computations with dependencies.Specifically, our analysis shows that the expected time to execute a fully strict computation on P processors using our work-stealing scheduler is T1/P + O(T ∞ , where T1 is the minimum serial execution time of the multithreaded computation and (T ∞ is the minimum execution time with an infinite number of processors. Moreover, the space required by the execution is at most S1P, where S1 is the minimum serial space requirement. We also show that the expected total communication of the algorithm is at most O(PT ∞( 1 + nd)Smax), where Smax is the size of the largest activation record of any thread and nd is the maximum number of times that any thread synchronizes with its parent. This communication bound justifies the folk wisdom that work-stealing schedulers are more communication efficient than their work-sharing counterparts. All three of these bounds are existentially optimal to within a constant factor.read more
Citations
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Journal ArticleDOI
Combining performance and priority for scheduling resizable parallel applications
TL;DR: Experimental results show that the scheduling policies significantly improve individual job turn around time as well as overall cluster utilization.
Proceedings ArticleDOI
A New Scalable Parallel Algorithm for Fock Matrix Construction
Xing Liu,Aftab Patel,Edmond Chow +2 more
TL;DR: This paper presents a new parallelization of HF calculations that uses fine grained tasks to balance the computation among large numbers of cores, but also uses a scheme to assign tasks to processes to reduce communication.
Proceedings ArticleDOI
Optimal (Randomized) Parallel Algorithms in the Binary-Forking Model
TL;DR: In the binary-forking model, tasks can only fork into two child tasks, but can do so recursively and asynchronously The tasks share memory, supporting reads, writes and test-and-sets costs are measured in terms of work (total number of instructions), and span (longest dependence chain) as discussed by the authors.
Proceedings ArticleDOI
Robust Large-Scale Machine Learning in the Cloud
TL;DR: A new scalable coordinate descent algorithm for generalized linear models whose convergence behavior is always the same, regardless of how much SCD is scaled out and regardless of the computing environment, which makes SCD highly robust and enables it to scale to massive datasets on low-cost commodity servers.
Proceedings ArticleDOI
SimMatrix: SIMulator for MAny-Task computing execution fabRIc at eXascale
TL;DR: A light-weight discrete event simulator, SimMatrix, which simulates job scheduling system comprising of millions of nodes and billions of cores/tasks, and which validated against two real systems and compared with SimGrid and GridSim in terms of resource consumption at scale.
References
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Journal ArticleDOI
Cilk: An Efficient Multithreaded Runtime System
Robert D. Blumofe,Christopher F. Joerg,Bradley C. Kuszmaul,Charles E. Leiserson,Keith H. Randall,Yuli Zhou +5 more
TL;DR: It is shown that on real and synthetic applications, the “work” and “critical-path length” of a Cilk computation can be used to model performance accurately, and it is proved that for the class of “fully strict” (well-structured) programs, the Cilk scheduler achieves space, time, and communication bounds all within a constant factor of optimal.
Journal ArticleDOI
Bounds for certain multiprocessing anomalies
TL;DR: In this paper, precise bounds are derived for several anomalies of this type in a multiprocessing system composed of many identical processing units operating in parallel, and they show that an increase in the number of processing units can cause an increased total length of time needed to process a fixed set of tasks.
Proceedings ArticleDOI
The implementation of the Cilk-5 multithreaded language
TL;DR: Cilk-5's novel "two-clone" compilation strategy and its Dijkstra-like mutual-exclusion protocol for implementing the ready deque in the work-stealing scheduler are presented.
Journal ArticleDOI
The Parallel Evaluation of General Arithmetic Expressions
TL;DR: It is shown that arithmetic expressions with n ≥ 1 variables and constants; operations of addition, multiplication, and division; and any depth of parenthesis nesting can be evaluated in time 4 log 2 + 10(n - 1) using processors which can independently perform arithmetic operations in unit time.