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Scalable and Conflict-Free NTT Hardware Accelerator Design: Methodology, Proof, and Implementation
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2023Number theoretic transform (NTT) is useful for the acceleration of polynomial multiplication, which is the main performance bottleneck in the next-generation cryptographic schemes.
Jianan Mu +10 more
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Timeloop: A Systematic Approach to DNN Accelerator Evaluation
IEEE International Symposium on Performance Analysis of Systems and Software, 2019This paper presents Timeloop, an infrastructure for evaluating and exploring the architecture design space of deep neural network (DNN) accelerators. Timeloop uses a concise and unified representation of the key architecture and implementation attributes
A. Parashar +9 more
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A 95.6-TOPS/W Deep Learning Inference Accelerator With Per-Vector Scaled 4-bit Quantization in 5 nm
IEEE Journal of Solid-State Circuits, 2023The energy efficiency of deep neural network (DNN) inference can be improved with custom accelerators. DNN inference accelerators often employ specialized hardware techniques to improve energy efficiency, but many of these techniques result in ...
Ben Keller +8 more
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SCNN: An accelerator for compressed-sparse convolutional neural networks
International Symposium on Computer Architecture, 2017Convolutional Neural Networks (CNNs) have emerged as a fundamental technology for machine learning. High performance and extreme energy efficiency are critical for deployments of CNNs, especially in mobile platforms such as autonomous vehicles, cameras ...
A. Parashar +8 more
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Hausmann, Ricardo +2 more
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ViA: A Novel Vision-Transformer Accelerator Based on FPGA
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2022Since Google proposed Transformer in 2017, it has made significant natural language processing (NLP) development. However, the increasing cost is a large amount of calculation and parameters.
Teng Wang +6 more
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Accelerating virtualization of accelerators
2021The use of specialized accelerators is among the most promising paths to better energy efficiency for computationally heavy workloads. However, current software and system support for accelerators is limited, and no production-ready solutions have yet been provided for accelerators to be efficiently accessed or shared in domains such as cloud ...
Yu, Hangchen, 0000-0002-6515-6271
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PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference
International Conference on Architectural Support for Programming Languages and Operating Systems, 2019Memristor crossbars are circuits capable of performing analog matrix-vector multiplications, overcoming the fundamental energy efficiency limitations of digital logic. They have been shown to be effective in special-purpose accelerators for a limited set
Aayush Ankit +10 more
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MATCHA: A Fast and Energy-Efficient Accelerator for Fully Homomorphic Encryption over the Torusa
Design Automation Conference, 2022Fully Homomorphic Encryption over the Torus (TFHE) allows arbitrary computations to happen directly on ciphertexts using homomorphic logic gates. However, each TFHE gate on state-of-theart hardware platforms such as GPUs and FPGAs is extremely slow ($\lt
Lei Jiang, Qian Lou, Nrushad Joshi
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Cancer, 1985
In the first third of this century, the prevailing concept was that malignant cells had a brief period of sensitivity and radiation treatments were ideally given in overall times of 2 weeks or less. Following the Second World War, routine treatment times were extended to 5 to 8 weeks to avoid severe acute normal tissue reactions and achieve higher ...
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In the first third of this century, the prevailing concept was that malignant cells had a brief period of sensitivity and radiation treatments were ideally given in overall times of 2 weeks or less. Following the Second World War, routine treatment times were extended to 5 to 8 weeks to avoid severe acute normal tissue reactions and achieve higher ...
openaire +2 more sources

