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Papers matching “floating-point precision” 9

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Possibilities and drawbacks using arbitrary precision numbers for structural analysis
2021 PAMM article Decision Sciences Probabilistic and Robust Engineering Design Open access

Simon Klarmann, Jens Wackerfuß

0

citations
On Correctness, Precision, and Performance in Quantitative Verification
2021 Lecture notes in computer science conference-paper Engineering Fault Detection and Control Systems Open access

Carlos E. Budde, Arnd Hartmanns, Michaela Klauck, Jan Křetínský, David Parker, Tim Quatmann, +1 more

39

citations
CLARINET: A quire-enabled RISC-V-based framework for posit arithmetic empiricism
2022 Journal of Systems Architecture article Computer Science Numerical Methods and Algorithms

Niraj N. Sharma, Riya Jain, Mohana Madhumita Pokkuluri, Sachin Patkar, Rainer Leupers, Rishiyur S. Nikhil, +1 more

18

citations
Brightening the Optical Flow through Posit Arithmetic
2021 International Symposium on Quality Electronic Design (ISQED) conference-paper Computer Science Numerical Methods and Algorithms Open access

Vinay Saxena, Ankitha Reddy, Jonathan Neudorfer, John Leroy Gustafson, Sangeeth Nambiar, Rainer Leupers, +1 more

11

citations
Design of High-Throughput Mixed-Precision CNN Accelerators on FPGA
2022 International Conference on Field Programmable Logic and Applications (FPL) conference-paper Computer Science Advanced Neural Network Applications

Cecilia Latotzke, Tim Ciesielski, Tobias Gemmeke

16

citations
Design of High-Throughput Mixed-Precision CNN Accelerators on FPGA
2022 arXiv (Cornell University) preprint Computer Science Advanced Neural Network Applications Open access

Cecilia Latotzke, Tim Ciesielski, Tobias Gemmeke

1

citations
Discrete Steps towards Approximate Computing
2022 International Symposium on Quality Electronic Design (ISQED) conference-paper Engineering Low-power high-performance VLSI design

Michael Gansen, Jie Lou, Florian Freye, Tobias Gemmeke, Farhad Merchant, Albert Zeyer, +3 more

8

citations
ExPAN(N)D: Exploring Posits for Efficient Artificial Neural Network Design in FPGA-Based Systems
2020 arXiv (Cornell University) preprint Computer Science Numerical Methods and Algorithms Open access

Suresh Nambi, Salim Ullah, Siva Satyendra Sahoo, Aditya Lohana, Farhad Merchant, Akash S. Kumar

4

citations
ExPAN(N)D: Exploring Posits for Efficient Artificial Neural Network Design in FPGA-Based Systems
2021 IEEE Access article Computer Science Numerical Methods and Algorithms Open access

Suresh Nambi, Salim Ullah, Siva Satyendra Sahoo, Aditya Lohana, Farhad Merchant, Akash S. Kumar

32

citations

9 results