A Design Methodology for the Next Generation Real-Time Vision Processors

Mori, Jones Y.; Werner, André; Shallufa, Arij; Fricke, Florian; Hübner, Michael

doi:10.1007/978-3-319-30481-6_2

Cited by 4 publications

(1 citation statement)

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“…It has been implemented by a few major vendors, including Nvidia, Intel, AMD, and Synopsys [28]. The authors of [5,9,25,31,32] focus on graph scheduling and design space exploration for heterogeneous systems consisting of GPUs, CPUs, and custom instruction-set architectures. Unlike the prior work, [24] suggests static OpenVX compilation for low-power embedded systems instead of runtime-library implementations.…”

Section: Related Workmentioning

confidence: 99%

HipaccVX: wedding of OpenVX and DSL-based code generation

Ozkan

Qiao

et al. 2020

J Real-Time Image Proc

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Writing programs for heterogeneous platforms optimized for high performance is hard since this requires the code to be tuned at a low level with architecture-specific optimizations that are most times based on fundamentally differing programming paradigms and languages. OpenVX promises to solve this issue for computer vision applications with a royalty-free industry standard that is based on a graph-execution model. Yet, the OpenVX ’ algorithm space is constrained to a small set of vision functions. This hinders accelerating computations that are not included in the standard. In this paper, we analyze OpenVX vision functions to find an orthogonal set of computational abstractions. Based on these abstractions, we couple an existing domain-specific language (DSL) back end to the OpenVX environment and provide language constructs to the programmer for the definition of user-defined nodes. In this way, we enable optimizations that are not possible to detect with OpenVX graph implementations using the standard computer vision functions. These optimizations can double the throughput on an Nvidia GTX GPU and decrease the resource usage of a Xilinx Zynq FPGA by 50% for our benchmarks. Finally, we show that our proposed compiler framework, called HipaccVX, can achieve better results than the state-of-the-art approaches Nvidia VisionWorks and Halide-HLS.

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Section: Related Workmentioning

confidence: 99%

HipaccVX: wedding of OpenVX and DSL-based code generation

Ozkan

Qiao

et al. 2020

J Real-Time Image Proc

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Domain Adaptive Processor Architectures

Fricke

Mahmood

Hoffmann

et al. 2020

Technologien Für Die Intelligente Automation

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The ongoing megatrends in industry and academia like the Internet of Things (IoT), the Industrial Internet of Things (IIoT) and Cyber-Physical Systems (CPS) present the developers of modern computer architectures with various challenges. A novel class of processors which provide more data throughput with a simultaneously tremendously reduced energy consumption are required as a backbone for these "Things". Additionally, the requirements of CPS like realtime, reliability, dependability, safety, and security are gaining in importance in these applications. This paper shows a brief overview of novel processor architectures providing high flexibility to adapt during design-and runtime to changing requirements of the application and the internal and external system status.© Der/die Herausgeber bzw. der/die Autor(en) 2020 J. Jasperneite, V. Lohweg Kommunikation und Bildverarbeitung in der Automation, (Hrsg.), Technologien für die intelligente Automation 12, https://doi.

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