Embedded Systems: ARM Programming and Optimization

by Jason D. Bakos

Overview

Embedded Systems: ARM Programming and Optimization combines an exploration of the ARM architecture with an examination of the facilities offered by the Linux operating system to explain how various features of program design can influence processor performance. It demonstrates methods by which a programmer can optimize program code in a way that does not impact its behavior but improves its performance. Several applications, including image transformations, fractal generation, image convolution, and computer vision tasks, are used to describe and demonstrate these methods. From this, the reader will gain insight into computer architecture and application design, as well as gain practical knowledge in the area of embedded software design for modern embedded systems. - Covers three ARM instruction set architectures, the ARMv6 and ARMv7-A, as well as three ARM cores, the ARM11 on the Raspberry Pi, Cortex-A9 on the Xilinx Zynq 7020, and Cortex-A15 on the NVIDIA Tegra K1 - Describes how to fully leverage the facilities offered by the Linux operating system, including the Linux GCC compiler toolchain and debug tools, performance monitoring support, OpenMP multicore runtime environment, video frame buffer, and video capture capabilities - Designed to accompany and work with most of the low cost Linux/ARM embedded development boards currently available

Product Details

ISBN-13:	9780128004128
Publisher:	Morgan Kaufmann Publishers
Publication date:	09/03/2015
Sold by:	Barnes & Noble
Format:	eBook
Pages:	320
File size:	6 MB

About the Author

Jason D. Bakos is a professor of Computer Science and Engineering at the University of South Carolina. He received a BS in Computer Science from Youngstown State University in 1999 and a PhD in Computer Science from the University of Pittsburgh in 2005. Dr. Bakos's research focuses on mapping data- and compute-intensive codes to high-performance, heterogeneous, reconfigurable, and embedded computer systems. His group works closely with FPGA-based computer manufacturers Convey Computer Corporation, GiDEL, and Annapolis Micro Systems, as well as GPU and DSP manufacturers NVIDIA, Texas Instruments, and Advantech. Dr. Bakos holds two patents, has published over 30 refereed publications in computer architecture and high-performance computing, was a winner of the ACM/DAC student design contest in 2002 and 2004, and received the US National Science Foundation (NSF) CAREER award in 2009. He is currently serving as associate editor for ACM Transactions on Reconfigurable Technology and Systems.
Jason D. Bakos is a professor of Computer Science and Engineering at the University of South Carolina. He received a BS in Computer Science from Youngstown State University in 1999 and a PhD in Computer Science from the University of Pittsburgh in 2005. Dr. Bakos’s research focuses on mapping data- and compute-intensive codes to high-performance, heterogeneous, reconfigurable, and embedded computer systems. His group works closely with FPGA-based computer manufacturers Convey Computer Corporation, GiDEL, and Annapolis Micro Systems, as well as GPU and DSP manufacturers NVIDIA, Texas Instruments, and Advantech. Dr. Bakos holds two patents, has published over 30 refereed publications in computer architecture and high-performance computing, was a winner of the ACM/DAC student design contest in 2002 and 2004, and received the US National Science Foundation (NSF) CAREER award in 2009. He is currently serving as associate editor for ACM Transactions on Reconfigurable Technology and Systems.

Table of Contents

1. The Linux/ARM Embedded Platform2. Multicore and Data-Level Optimization: OpenMP and SIMD3. Arithmetic Optimization and the Linux Framebuffer4. Memory Optimization and Video Processing5. Embedded Heterogeneous Programming with OpenCLA. Adding PMU Support to Raspbian for the Generation 1 Raspberry PiB. NEON Intrinsic ReferenceC. OpenCL Reference

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From the Publisher

Provides a graphics and performance-oriented approach to embedded computing on a low-cost, ARM-based platform