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A scheme for accelerating image processing algorithms using SIMD for ARM Cortex A based systems

机译:一种用于使用SIMD进行ARM皮质基于SIMD的图像处理算法的方案

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Increasing computational requirements in embedded mobile devices, especially with regard to image processing, necessitates the use of hardware acceleration to handle higher throughputs. ARM Cortex A series of processors, which are present in a majority of mobile devices such as smartphones, feature a single instruction multiple data (SIMD) coprocessor called NEON. The wide SIMD architecture enables the parallelization of various image processing operations and algorithms, resulting in significant improvements in the system throughput. This paper discusses the use of NEON Intrinsics, a C language implementation of the NEON SIMD instruction set, which is an extension of the ARM instruction set, allowing the seamless integration of optimized image processing libraries with application code written in higher level languages, while maintaining performance comparable to hand optimized assembly language libraries. Several image processing operations and algorithms optimized using NEON Intrinsics are benchmarked on a test bench as well as real world hardware platforms to validate the acceleration achieved in image processing tasks.
机译:提高嵌入式移动设备中的计算要求,特别是关于图像处理,需要使用硬件加速来处理更高的吞吐量。 ARM Cortex A系列处理器,这些处理器存在于大多数移动设备(如智能手机)中,具有单个指令多个数据(SIMD)协处理器,称为氖。宽的SIMD架构能够并行化各种图像处理操作和算法,从而产生系统吞吐量的显着改进。本文讨论了霓虹Instinsics的使用,霓虹灯SIMD指令集的C语言实现,它是ARM指令集的扩展,允许使用更高级语言编写的应用程序代码的优化图像处理库的无缝集成,同时保持性能可与手动优化的汇编语言库相媲美。使用霓虹Instinsics优化的几种图像处理操作和算法在测试台以及真实世界硬件平台上是基准测试,以验证在图像处理任务中实现的加速度。

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