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Synopsis
The embedded systems are bound to real-time constraints with determinism and latency as critical metrics. Generally RTOS implemented through software are found to introduce a significant amount of performance degradation. Task scheduling, resource allocation and de-allocation, deadlock detection and other OS/API functions steal execution time from the tasks executing on the CPU. Scheduling algorithms play an important role in the design of real-time systems as it improves the usage of system resources. The performance loss comes in the form of increased processor utilization, response time, real-time jitter, memory footprint can be reduced significantly by utilizing latest Fuzzy Inference System based adaptive FPGA hardware task scheduler for multiprocessor systems which minimizes the processor time for scheduling activity. An adaptive framework with feedback mechanism allows processors dynamically controlled the sharing of task on multiprocessors systems. The increased computational overheads resulted can be compensated by exploiting the parallelism of the hardware and thus improves the overall performance of RTOS and Embedded system.
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Cognitive Scheduler
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LAP LAMBERT Academic Publishing Apr 2021, 2021
ISBN 10: 620384117X
ISBN 13: 9786203841176
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The embedded systems are bound to real-time constraints with determinism and latency as critical metrics. Generally RTOS implemented through software are found to introduce a significant amount of performance degradation. Task scheduling, resource allocation and de-allocation, deadlock detection and other OS/API functions steal execution time from the tasks executing on the CPU. Scheduling algorithms play an important role in the design of real-time systems as it improves the usage of system resources. The performance loss comes in the form of increased processor utilization, response time, real-time jitter, memory footprint can be reduced significantly by utilizing latest Fuzzy Inference System based adaptive FPGA hardware task scheduler for multiprocessor systems which minimizes the processor time for scheduling activity. An adaptive framework with feedback mechanism allows processors dynamically controlled the sharing of task on multiprocessors systems. The increased computational overheads resulted can be compensated by exploiting the parallelism of the hardware and thus improves the overall performance of RTOS and Embedded system. 240 pp. Englisch. Seller Inventory # 9786203841176
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Cognitive Scheduler
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LAP LAMBERT Academic Publishing, 2021
ISBN 10: 620384117X
ISBN 13: 9786203841176
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Cognitive Scheduler | FPGA based Adaptive Hardware Scheduler
Published by
LAP LAMBERT Academic Publishing, 2021
ISBN 10: 620384117X
ISBN 13: 9786203841176
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Taschenbuch. Condition: Neu. Cognitive Scheduler | FPGA based Adaptive Hardware Scheduler | Dinesh Harkut (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203841176 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 120063681
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Cognitive Scheduler
Published by
LAP LAMBERT Academic Publishing Apr 2021, 2021
ISBN 10: 620384117X
ISBN 13: 9786203841176
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Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware -The embedded systems are bound to real-time constraints with determinism and latency as critical metrics. Generally RTOS implemented through software are found to introduce a significant amount of performance degradation. Task scheduling, resource allocation and de-allocation, deadlock detection and other OS/API functions steal execution time from the tasks executing on the CPU. Scheduling algorithms play an important role in the design of real-time systems as it improves the usage of system resources. The performance loss comes in the form of increased processor utilization, response time, real-time jitter, memory footprint can be reduced significantly by utilizing latest Fuzzy Inference System based adaptive FPGA hardware task scheduler for multiprocessor systems which minimizes the processor time for scheduling activity. An adaptive framework with feedback mechanism allows processors dynamically controlled the sharing of task on multiprocessors systems. The increased computational overheads resulted can be compensated by exploiting the parallelism of the hardware and thus improves the overall performance of RTOS and Embedded system.Books on Demand GmbH, Überseering 33, 22297 Hamburg 240 pp. Englisch. Seller Inventory # 9786203841176
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Cognitive Scheduler : FPGA based Adaptive Hardware Scheduler
Published by
LAP LAMBERT Academic Publishing, 2021
ISBN 10: 620384117X
ISBN 13: 9786203841176
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The embedded systems are bound to real-time constraints with determinism and latency as critical metrics. Generally RTOS implemented through software are found to introduce a significant amount of performance degradation. Task scheduling, resource allocation and de-allocation, deadlock detection and other OS/API functions steal execution time from the tasks executing on the CPU. Scheduling algorithms play an important role in the design of real-time systems as it improves the usage of system resources. The performance loss comes in the form of increased processor utilization, response time, real-time jitter, memory footprint can be reduced significantly by utilizing latest Fuzzy Inference System based adaptive FPGA hardware task scheduler for multiprocessor systems which minimizes the processor time for scheduling activity. An adaptive framework with feedback mechanism allows processors dynamically controlled the sharing of task on multiprocessors systems. The increased computational overheads resulted can be compensated by exploiting the parallelism of the hardware and thus improves the overall performance of RTOS and Embedded system. Seller Inventory # 9786203841176
Quantity: 1 available