HW/SW Co-design Toolset for Customization of Exposed Datapath Processors

Jääskeläinen, Pekka; Viitanen, Timo; Takala, Jarmo; Berg, Heikki

doi:10.1007/978-3-319-49679-5_8

Cited by 35 publications

(22 citation statements)

References 8 publications

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“…In this work, the TCE toolchain (TTA-based Co-design Environment [20]) was employed for design and optimization of the processor. The processor was later implemented and tested for verification on an FPGA.…”

Section: Methodsmentioning

confidence: 99%

An Embedded Programmable Processor for Compressive Sensing Applications

Safarpour

Hautala

Silvén

2018

2018 IEEE Nordic Circuits and Systems Conference (NORCAS): NORCHIP and International Symposium of System-on-Chip (SoC)

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An application specific programmable processor is designed based on the analysis of a set of greedy recovery Compressive Sensing (CS) algorithms. The solution is flexible and customizable for a wide range of problem dimensions, as well as algorithms. The versatility of the approach is demonstrated by implementing Orthogonal Matching Pursuits, Approximate Messaging Passing and Normalized Iterative Hard Thresholding algorithms, all using a high-level language. Transported Triggered Architecture (TTA) framework is employed for the efficient implementation of macro operations shared by the algorithms. The performance of the CS algorithms on ARM Cortex-A15 and NIOS II processors has also been investigated, and empirical comparisons are presented. The flexible hardware design implemented on an FPGA achieves up to 7.80Ksample/s recovery at a power dissipation of 42μJ/sample and beats both ARM and NIOS in total power consumption.

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Section: Methodsmentioning

confidence: 99%

An Embedded Programmable Processor for Compressive Sensing Applications

Safarpour

Hautala

Silvén

2018

2018 IEEE Nordic Circuits and Systems Conference (NORCAS): NORCHIP and International Symposium of System-on-Chip (SoC)

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“…For example, the compiler of the TCE toolset [7] implements a pre-pass register allocation followed by scheduling, since the complexities of inserting spill code possibly creating a cyclic dependency between register allocation and scheduling stages.…”

Section: Challenges In Exposed Datapath Code Generationmentioning

confidence: 99%

“…Most existing compilers of these architectures have C/C++ or an OpenCL C frontend with a target specific custom backend [12], which is not easy to extend. To the best of our knowledge, the TCE toolset [7] seems an ideal fit for this case as it is closely related to our use-case and has a robust compiler (C, C++, and OpenCL) accompanied with a rich set of supporting tools such as simulator, debugger, and GUI based processor design tools. Extending TCE to support the generic machine-model presented in Section 2.3 will benefit the architectures listed in Table 1.…”

Section: Towards Generic Code Generation Toolsmentioning

confidence: 99%

Towards Efficient Code Generation for Exposed Datapath Architectures

Vadivel

Jordans

Stujik

et al. 2019

Proceedings of the 22nd International Workshop on Software and Compilers for Embedded Systems

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“…The second type consists of dedicated ALMARVI platforms created by the various partners of the project. These platforms are: 1. the rVEX dynamically adaptive core created by TUDelft (Delft University of Technology) [2,3], 2. the TCE customizable processor tool chain created by TUT (Tampere University of Technology) [4], 3. the edkDSP accelerated hardware processors created by UTIA (Institute of Information Theory and Automation) [5]. The hardware processing platforms used by the ALMARVI partners span a wide spectrum of design space alternatives as shown in Figure 2.…”

Section: System Stackmentioning

confidence: 99%

ALMARVI System Solution for Image and Video Processing in Healthcare, Surveillance and Mobile Applications

Al-Ars

Vlugt

Jääskeläinen

et al. 2018

J Sign Process Syst

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ALMARVI is a collaborative European research project funded by Artemis involving 16 industrial as well as academic partners across 4 countries, working together to address various computational challenges in image and video processing in 3 application domains: healthcare, surveillance and mobile. This paper is an editorial for a special issue discussing the integrated system created by the partners to serve as a cross-domain solution for the project. The paper also introduces the partner articles published in this special issue to discuss the various technological developments achieved within ALMARVI spanning all system layers, from hardware to applications. We illustrate the challenges faced within the project based on use cases from the three targeted application domains, and how these can address the 4 main project objectives addressing 4 challenges faced by high performance image and video processing systems: massive data rate, low power consumption, composability and robustness. We present a system stack composed of algorithms, design frameworks and platforms as a solution to these challenges. Finally, the use cases from the three different application domains are mapped on the system stack solution and are evaluated based on their performance for each of the 4 ALMARVI objectives.

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HW/SW Co-design Toolset for Customization of Exposed Datapath Processors

Cited by 35 publications

References 8 publications

An Embedded Programmable Processor for Compressive Sensing Applications

An Embedded Programmable Processor for Compressive Sensing Applications

Towards Efficient Code Generation for Exposed Datapath Architectures

ALMARVI System Solution for Image and Video Processing in Healthcare, Surveillance and Mobile Applications

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