Automatic self-allocating threads (ASAT) on an SGI Challenge

Severance, Charles; Enbody, Richard

doi:10.1109/icpp.1996.538568

Cited by 7 publications

(10 citation statements)

References 5 publications

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“…This solution has the problem that the view of the status of the system obtained by each application can be different and nothing ensures that the response given by the individual applications can help to solve the global problem of the system. A similar mechanism was also proposed in [32].…”

Section: Sharing Information With the Upper Levelssupporting

confidence: 72%

Job Scheduling Strategies for Parallel Processing

2000

Lecture Notes in Computer Science

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E d i t e d b y G . G o o s , J . H a r t m a n i s a n d J . v a n L e e u w e n I P D P S 2 0 0 0 W o r k s h o p , J S S P P 2 0 0 0 C a n c u n , M e x i c o , M a y 1 , 2 0 0 0 P r o c e e d i n g s 1 3S e r i e s E d i t o r s G e r h a r d G o o s , K a r l s r u h e U n i v e r s i t y , G e r m a n y J u r i s H a r t m a n i s , C o r n e l l U n i v e r s i t y , N Y , U S A J a n v a n L e e u w e n , U t r e c h t U n i v e r s i t y , T h e N e t h e r l a n d s V o l u m e E d i t o r s D r o r G . F e i t e l s o n T h e H e b r e w U n i v e r s i t y S c h o o l o f C o m p u t e r S c i e n c e a n d E n g i n e e r i n g 9 1 9 0 4 J e r u s a l e m , I s r a e l E -m a i l : f e i t @ c s . h u j i . a c . i l L a r r y R u d o l p h M a s s a c h u s e t t s I n s t i t u t e o f T e c h n o l o g y L a b o r a t o r y f o r C o m p u t e r S c i e n c e C a m b r i d g e , M A 0 2 1 3 9 , U S A E -m a i l : r u d o l p h @ l c s . m i t . e d u C a t a l o g i n g -i n -P u b l i c a t i o n D a t a a p p l i e d f o r D i e D e u t s c h e B i b l i o t h e k -C I P -E i n h e i t s a u f n a h m e J o b s c h e d u l i n g s t r a t e g i e s f o r p a r a l l e l p r o c e s s i n g : p r o c e e d i n g s / I P D P S 2 0 0 0 w o r k s h o p , J S S P P 2 0 0 0 , C a n c u n , M e x i c o , M a y 1 , 2 0 0 0 . D r o r G . F e i t e l s o n ; L a r r y R u d o l p h ( e d . ) . -B e r l i n ; H e i d e l b e r g ; N e w Y o r k ; B a r c e l o n a ; H o n g K o n g ; L o n d o n ; M i l a n ; P a r i s ; S i n g a p o r e ; T o k y o : S p r i n g e r , 2 0 0 0 ( L e c t u r e n o t e s i n c o m p u t e r s c i e n c e ; V o l . 1 9 1 1 ) I S B N 3 -5 4 0 -4 1 1 2 0 -8

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Section: Sharing Information With the Upper Levelssupporting

confidence: 72%

Job Scheduling Strategies for Parallel Processing

2000

Lecture Notes in Computer Science

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“…Based on a run-time decision, these systems allocate either one processor or all available processors to the application program. Other systems use load information to allocate as many processors as possible without overloading the system [20][21][22]. A few systems combine both the program behavior and the system load aspect in allocating processors to parallel loops [23].…”

Section: Related Workmentioning

confidence: 99%

Dynamically adapting to system load and program behavior in multiprogrammed multiprocessor systems

Kazi

Lilja

2002

Concurrency and Computation

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SUMMARYParallel execution of application programs on a multiprocessor system may lead to performance degradation if the workload of a parallel region is not large enough to amortize the overheads associated with the parallel execution. Furthermore, if too many processes are running on the system in a multiprogrammed environment, the performance of the parallel application may degrade due to resource contention. This work proposes a comprehensive dynamic processor allocation scheme that takes both program behavior and system load into consideration when dynamically allocating processors. This mechanism was implemented on the Solaris operating system to dynamically control the execution of parallel C and Java application programs. Performance results show the effectiveness of this scheme in dynamically adapting to the current execution environment and program behavior, and that it outperforms a conventional time-shared system.

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“…Other studies, including those by Tucker et al [14,15], base thread allocation on specific synchronization mechanisms in the code, and thus require that the programmer of the system use these synchronization mechanisms as the basis of an explicit parallel programming model. Severance et al have published additional work on ASAT, a similar approach, as implemented for the SGI Challenge and the Convex Exemplar [16,17]. Our approach extends significantly from these by using on-the-fly application performance information to guide decisions about processor/program assignments.…”

Section: Related Workmentioning

confidence: 99%

Adaptive parallelism in compiler-parallelized code

Hall¹,

Martonosi

1998

Concurrency: Pract. Exper.

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As moderate‐scale multiprocessors become widely used, we foresee an increased demand for effective compiler parallelization and efficient management of parallelism. While parallelizing compilers are achieving success at identifying parallelism, they are less adept at predetermining the degree of parallelism in different program phases. Thus, a compiler‐parallelized application may execute on more processors than it can effectively use – a waste of computational resources that becomes more acute as the number of processors increases, particularly for systems used as multiprogrammed compute servers. This paper examines the dynamic parallelism behavior of multiprogrammed workloads using programs from the Specfp95 and Nas benchmark suites, automatically parallelized by the Stanford SUIF compiler. Our results demonstrate that even the programs with good overall speedups display wide variability in the number of processors each phase (or loop) can exploit. We propose and evaluate a run‐time system mechanism that dynamically adjusts the number of processors used by a compiler‐parallelized application, responding to observed performance during the program's execution. Programs can thus adapt processor usage as they run, responding both to poor parallelism within certain parts of their code, and also to heavy multiprogramming loads during the execution. This mechanism improves workload performance up to 33% over one‐at‐a‐time runs of the workload programs. © 1998 John Wiley & Sons, Ltd.

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Automatic self-allocating threads (ASAT) on an SGI Challenge

Cited by 7 publications

References 5 publications

Job Scheduling Strategies for Parallel Processing

Job Scheduling Strategies for Parallel Processing

Dynamically adapting to system load and program behavior in multiprogrammed multiprocessor systems

Adaptive parallelism in compiler-parallelized code

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