IEICE TRANSACTIONS on Fundamentals
An Overlapped Scheduling Method for an Iterative Processing Algorithm with Conditional Operations
Summary :
One of the ways to execute a processing algorithm in high speed is parallel processing on multiple computing resources such as processors and functional units. To identify the minimum number of computing resources, the most important is the scheduling to determine when each operation in the processing algorithm is executed. Among feasible schedules satisfying all the data dependencies in the processing algorithm, an overlapped schedule can achieve the fastest execution speed for an iterative processing algorithm. In the case of processing algorithms with operations which are executed on some conditions, computing resources can be shared by those conditional operations. In this paper, we propose a scheduling method which derives an overlapped schedule where the required number of computing resources is minimized by considering the sharing by conditional operations.
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- IEICE TRANSACTIONS on Fundamentals Vol.E81-A No.3 pp.429-438
- Publication Date
- 1998/03/25
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- Special Section PAPER (Special Section of Selected Papers from the 10th Karuizawa Workshop on Circuits and Systems)
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Kazuhito ITO, Tatsuya KAWASAKI, "An Overlapped Scheduling Method for an Iterative Processing Algorithm with Conditional Operations" in IEICE TRANSACTIONS on Fundamentals,
vol. E81-A, no. 3, pp. 429-438, March 1998, doi: .
Abstract: One of the ways to execute a processing algorithm in high speed is parallel processing on multiple computing resources such as processors and functional units. To identify the minimum number of computing resources, the most important is the scheduling to determine when each operation in the processing algorithm is executed. Among feasible schedules satisfying all the data dependencies in the processing algorithm, an overlapped schedule can achieve the fastest execution speed for an iterative processing algorithm. In the case of processing algorithms with operations which are executed on some conditions, computing resources can be shared by those conditional operations. In this paper, we propose a scheduling method which derives an overlapped schedule where the required number of computing resources is minimized by considering the sharing by conditional operations.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e81-a_3_429/_p
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@ARTICLE{e81-a_3_429,
author={Kazuhito ITO, Tatsuya KAWASAKI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={An Overlapped Scheduling Method for an Iterative Processing Algorithm with Conditional Operations},
year={1998},
volume={E81-A},
number={3},
pages={429-438},
abstract={One of the ways to execute a processing algorithm in high speed is parallel processing on multiple computing resources such as processors and functional units. To identify the minimum number of computing resources, the most important is the scheduling to determine when each operation in the processing algorithm is executed. Among feasible schedules satisfying all the data dependencies in the processing algorithm, an overlapped schedule can achieve the fastest execution speed for an iterative processing algorithm. In the case of processing algorithms with operations which are executed on some conditions, computing resources can be shared by those conditional operations. In this paper, we propose a scheduling method which derives an overlapped schedule where the required number of computing resources is minimized by considering the sharing by conditional operations.},
keywords={},
doi={},
ISSN={},
month={March},}
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TY - JOUR
TI - An Overlapped Scheduling Method for an Iterative Processing Algorithm with Conditional Operations
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 429
EP - 438
AU - Kazuhito ITO
AU - Tatsuya KAWASAKI
PY - 1998
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E81-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 1998
AB - One of the ways to execute a processing algorithm in high speed is parallel processing on multiple computing resources such as processors and functional units. To identify the minimum number of computing resources, the most important is the scheduling to determine when each operation in the processing algorithm is executed. Among feasible schedules satisfying all the data dependencies in the processing algorithm, an overlapped schedule can achieve the fastest execution speed for an iterative processing algorithm. In the case of processing algorithms with operations which are executed on some conditions, computing resources can be shared by those conditional operations. In this paper, we propose a scheduling method which derives an overlapped schedule where the required number of computing resources is minimized by considering the sharing by conditional operations.
ER -
English
