Approximate Computing on FPGAs
ACoF
Approximate Computing systematically exploits the trade-off between accuracy, power/energy consumption, performance, and cost of many applications of daily life, e.g., computer vision, machine learning, multimedia, big data analysis and gaming. Computing results approximately is a viable approach here thanks to inherent human perceptual limitations, redundancy, or noise in input data.In this project, we want to investigate novel techniques for the design and optimization of approximate logic circuits for FPGA (field-programmable gate array) targets. These devices are known to perfectly combine high performance of hardware designs with the re-programmability of software and are used in many products of daily life and even cloud servers. The goal of our research is a) to investigate novel techniques for function approximation exploiting FPGA artifacts, i.e., DPS blocks and BRAM, b) to study new error metrics and a calculus for error propagation in networks of approximate arithmetic modules, c) to develop novel FPGA-specific optimization techniques for design space exploration and synthesis of approximate multi-output Boolean functions, and d) study how to integrate error modeling and analysis techniques into existing high-level programming languages and subsequent synthesis of approximate Verilog or VHDL designs.
Publikationen
BDD-based Error Metric Analysis, Computation and Optimization
In: IEEE Access 10 (2022), p. 14013 - 14028
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2022.3140557
URL: https://ieeexplore.ieee.org/abstract/document/9669272
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Approximate Computing Extensions for the Clash HDL Compiler
Workshop Methoden und Beschreibungssprachen zur Modellierung und Verifikation von Schaltungen und Systemen (virtuelle Konferenz, 18. March 2021 - 19. March 2021)
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Design and Error Analysis of Accuracy-configurable Sequential Multipliers via Segmented Carry Chains
In: it - Information Technology (2022)
ISSN: 1611-2776
DOI: 10.1515/itit-2021-0040
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Design Space Exploration of Time, Energy, and Error Rate Trade-offs for CNNs using Accuracy-Programmable Instruction Set Processors
2nd International Workshop on IoT, Edge, and Mobile for Embedded Machine Learning (ITEM) (Virtual Event, 13. September 2021 - 17. September 2021)
In: Springer, Cham (ed.): Joint European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021), Switzerland: 2021
DOI: 10.1007/978-3-030-93736-2_29
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Probability-based DSE of Approximated LUT-based FPGA Designs
15th IEEE Dallas Circuits and Systems Conference (Dallas, 17. June 2022 - 19. June 2022)
DOI: 10.1109/dcas53974.2022.9845591
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DSP-Packing: Squeezing Low-precision Arithmetic into FPGA DSP Blocks
International Conference on Field Programmable Logic and Applications (FPL) (Belfast, United Kingdom, 29. August 2022 - 2. September 2022)
In: IEEE Proceedings of the 32nd International Conference on Field Programmable Logic and Applications 2022
DOI: 10.1109/FPL57034.2022.00035
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Efficient Hardware Acceleration of Sparsely Active Convolutional Spiking Neural Networks
International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS) (Shanghai, 7. October 2022 - 14. October 2022)
DOI: 10.1109/tcad.2022.3197512
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Fast Approximate AIG-Based Synthesis
International Workshop on Boolean Problems (Bremen, 22. September 2022 - 23. September 2022)
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A fast BDD Minimization Framework for Approximate Computing
Design, Automation and Test in Europe (ALPEXPO, Grenoble, France, 9. March 2020 - 13. March 2020)
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Efficient Hardware Acceleration of Sparsely Active Convolutional Spiking Neural Networks
In: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 41 (2022), p. 3767 - 3778
ISSN: 0278-0070
DOI: 10.1109/TCAD.2022.3197512
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Efficient Table-based Function Approximation on FPGAs using Interval Splitting and BRAM Instantiation
In: ACM Transactions on Embedded Computing Systems 22 (2023), p. 1-24
ISSN: 1539-9087
DOI: 10.1145/3580737
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Fast Approximate AIG-Based Synthesis
In: Rolf Drechsler, Sebastian Huhn (ed.): Advanced Boolen Techniques, Springer, 2023, p. 17 -- 32
ISBN: 978-3-031-28915-6
DOI: 10.1007/978-3-031-28916-3
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