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Hardware acceleration of EDA algorithms : custom ICs, FPGAs and GPUs

Author: Kanupriya Gulati; Sunil P Khatri
Publisher: New York ; London : Springer, ©2010.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Hardware Acceleration of EDA Algorithms: Custom ICs, FPGAs and GPUs Kanupriya Gulati Sunil P. Khatri This book deals with the acceleration of EDA algorithms using hardware platforms such as Custom ICs, FPGAs and GPUs. Widely applied CAD algorithms are studied for potential acceleration on these platforms. Coverage includes discussion of conditions under which it is preferable to use one platform over another, e.g.,  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Gulati, Kanupriya.
Hardware acceleration of EDA algorithms.
New York ; London : Springer, ©2010
(OCoLC)499067154
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Kanupriya Gulati; Sunil P Khatri
ISBN: 9781441909442 1441909443
OCLC Number: 663096916
Description: 1 online resource (xxii, 192 pages) : illustrations
Contents: Alternative Hardware Platforms --
Hardware Platforms --
GPU Architecture and the CUDA Programming Model --
Control Dominated Category --
Accelerating Boolean Satisfiability on a Custom IC --
Accelerating Boolean Satisfiability on an FPGA --
Accelerating Boolean Satisfiability on a Graphics Processing Unit --
Control Plus Data Parallel Applications --
Accelerating statistical static Timing Analysis Using Graphics Processors --
Accelerating Fault Simulation Using Graphics Processors --
Fault Table Generation Using Graphics Processors --
Accelerating Circuit Simulation Using Graphics Processors --
Automated Generation of GPU Code --
Automated Approach for Graphics Processor Based Software Acceleration --
Conclusions.
Responsibility: Kanupriya Gulati, Sunil P. Khatri.

Abstract:

This text covers the acceleration of EDA algorithms using hardware platforms such as FPGAs and GPUs. In it, widely applied CAD algorithms are evaluated and compared for potential acceleration on  Read more...

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