Newly published; Embedded Computing for High Performance:…
Working with popular hardware, including Xilinx and ARM, it offers a comprehensive description of techniques for mapping computations expressed in programming languages such as C or MATLAB to high-performance embedded architectures consisting of multiple CPUs, GPUs, and reconfigurable hardware (FPGAs). The authors demonstrate a domain-specific language (LARA) that facilitates retargeting to multiple computing systems using the same source code. In this way, users can decouple original application code from transformed code and enhance productivity and program portability. After reading this book, engineers will understand the processes, methodologies, and best practices needed for the development of applications for high-performance embedded computing systems.
The text;
– Focuses on maximizing performance while managing energy consumption in embedded systems
– Explains how to retarget code for heterogeneous systems with GPUs and FPGAs
– Demonstrates a domain-specific language that facilitates migrating and retargeting existing applications to modern systems
– Includes downloadable slides, tools, and tutorials
It is aimed at computer engineers and computer scientists as well as electrical engineers working on embedded, parallel, or FPGA systems; and is also intended for students in these areas.
Published at €62.86 by Elsevier; https://www.elsevier.com/books/isbn/9780128041895
Authors
João Cardoso is Associate Professor, Department of Informatics Engineering (DEI), Faculty of Engineering, University of Porto, Portugal.
José Gabriel Coutinho is Research Associate, Imperial College (London). He is involved in the EU FP7 HARNESS project to integrate heterogeneous hardware and network technologies into data centre platforms, to vastly increase performance, reduce energy consumption, and lower cost profiles.
Pedro Diniz is Researcher with the University of Southern California’s Information Sciences Institute (USC/ISI) and an Assistant Professor of Computer Science at the University of Southern California in Los Angeles, California. He has over many years been involved in the scientific community in the area of high-performance computing, reconfigurable and field-programmable computing.
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