Advanced Multicore Systems-On-Chip: Architecture, On-Chip Network, Design By 作者: Abderazek Ben Abdallah ISBN-10 书号: 9811060916 ISBN-13 书号: 9789811060915 Edition 版本: 1st ed. 2017 出版日期: 2017-09-12 pages 页数: (273 ) Springer 出版超清 From basic architecture, interconnection, and parallelization to power optimization, this book provides a comprehensive description of emerging multicore systems-on-chip (MCSoCs) hardware and software design. Highlighting both fundamentals and advanced software and hardware design, it can serve as a primary textbook for advanced courses in MCSoCs design and embedded systems. The first three chapters introduce MCSoCs architectures, present design challenges and conventional design methods, and describe in detail the main building blocks of MCSoCs. Chapters 4, 5, and 6 discuss fundamental and advanced on-chip interconnection network technologies for multi and many core SoCs, enabling readers to understand the microarchitectures for on-chip routers and network interfaces that are essential in the context of latency, area, and power constraints. With the rise of multicore and many-core systems, concurrency is becoming a major issue in the daily life of a programmer. Thus, compiler and software development tools are critical in helping programmers create high-performance software. Programmers should make sure that their parallelized program codes will not cause race condition, memory-access deadlocks, or other faults that may crash their entire systems. As such, Chapter 7 describes a novel parallelizing compiler design for high-performance computing. Chapter 8 provides a detailed investigation of power reduction techniques for MCSoCs at component and network levels. It discusses energy conservation in general hardware design, and also in embedded multicore system components, such as CPUs, disks, displays and memories. Lastly, Chapter 9 presents a real embedded MCSoCs system design targeted for health monitoring in the elderly.
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讲解如何通过TASKING 创建一个支持英飞凌芯片的多核例程,讲解细致到位,值得参考和借鉴。推荐大家下载,如需相关英飞凌资源也可以直接私信我,欢迎沟通!!!!
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AutoDock-GPU:适用于GPU和其他加速器的AutoDock 关于 OpenCL和Cuda加速版的AutoDock4.2.6。 它通过在多个计算单元上并行处理配体-受体姿势来利用其令人尴尬的可并行LGA。 OpenCL版本是与TU-Darmstadt合作开发的,能够针对CPU,GPU和FPGA架构。 Cuda版本是与Nvidia合作开发的,以便在Oak Ridge国家实验室(ORNL)峰会上运行AutoDock-GPU,其中包括Jubilee Development公司的Aaron Scheinberg开发的批量配体管线。 引文 使用GPU和基于梯度的本地搜索加速AutoDock4, 2021,10.1021 / acs.jctc.0c01006 查看 特征 基于梯度的本地搜索方法(例如ADADELTA),以及AutoDock 4中Solis-Wets的改进版本。 它针
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When Good Enough Is Better: Energy-Aware Scheduling for Multicore Servers
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Multicore and GPU Programming An Integrated Approach.pdf
2019-12-21 21:16:09 36.56MB GPU Qt
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