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pro vyhledávání: '"Ullah, Salim"'
Multiplication is one of the widely used arithmetic operations in a variety of applications, such as image/video processing and machine learning. FPGA vendors provide high-performance multipliers in the form of DSP blocks. These multipliers are not o
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A83401
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With the increasing application of machine learning (ML) algorithms in embedded systems, there is a rising necessity to design low-cost computer arithmetic for these resource-constrained systems. As a result, emerging models of computation, such as a
Externí odkaz:
http://arxiv.org/abs/2309.13445
The rising usage of AI and ML-based processing across application domains has exacerbated the need for low-cost ML implementation, specifically for resource-constrained embedded systems. To this end, approximate computing, an approach that explores t
Externí odkaz:
http://arxiv.org/abs/2309.12830
Autor:
Ullah, Salim
From the initial computing machines, Colossus of 1943 and ENIAC of 1945, to modern high-performance data centers and Internet of Things (IOTs), four design goals, i.e., high-performance, energy-efficiency, resource utilization, and ease of programmab
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A78708
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https://tud.qucosa.de/api/qucosa%3A78708/attachment/ATT-0/
Autor:
Mehmood, Shah, Dawit, Hewan, Hussain, Zahid, Ullah, Salim, Ullah, Ismat, Liu, Xingzhu, Liu, Yuanshan, Cao, Yi, Wang, Zixun, Pei, Renjun
Publikováno v:
In Chemical Engineering Journal 1 September 2024 495
Publikováno v:
ACM Great Lakes Symposium on VLSI (GLSVLSI) 2020
The ever-increasing quest for data-level parallelism and variable precision in ubiquitous multimedia and Deep Neural Network (DNN) applications has motivated the use of Single Instruction, Multiple Data (SIMD) architectures. To alleviate energy as th
Externí odkaz:
http://arxiv.org/abs/2011.01148
Autor:
Nambi, Suresh, Ullah, Salim, Lohana, Aditya, Sahoo, Siva Satyendra, Merchant, Farhad, Kumar, Akash
The recent advances in machine learning, in general, and Artificial Neural Networks (ANN), in particular, has made smart embedded systems an attractive option for a larger number of application areas. However, the high computational complexity, memor
Externí odkaz:
http://arxiv.org/abs/2010.12869
Akademický článek
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Autor:
Hussain, Zahid, Ullah, Ismat, Liu, Xingzhu, Mehmood, Shah, Wang, Li, Ma, Fanshu, Ullah, Salim, Lu, Zhongzhong, Wang, Zixun, Pei, Renjun
Publikováno v:
In Biomaterials Advances December 2023 155