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ORCIDWojciech Romaszkan
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2020 – today
- 2024
[j4]Wojciech Romaszkan
, Jiyue Yang, Alexander Graening, Vinod Kurian Jacob, Jishnu Sen, Sudhakar Pamarti, Puneet Gupta:
SCIMITAR: Stochastic Computing In-Memory In-Situ Tracking ARchitecture for Event-Based Cameras. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 43(11): 4214-4225 (2024)- [c3]Jiyue Yang, Alexander Graening, Wojciech Romaszkan, Vinod K. Jacob, Puneet Gupta, Sudhakar Pamarti:
A 278-514M Event/s ADC-Less Stochastic Compute-In-Memory Convolution Accelerator for Event Camera. VLSI Technology and Circuits 2024: 1-2 - 2023
- [b1]Wojciech Romaszkan:
Efficient Machine Learning Acceleration at the Edge. University of California, Los Angeles, USA, 2023 - [j3]Tianmu Li, Wojciech Romaszkan, Sudhakar Pamarti, Puneet Gupta:
REX-SC: Range-Extended Stochastic Computing Accumulation for Neural Network Acceleration. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(12): 4423-4435 (2023) - [i2]Ravit Sharma, Wojciech Romaszkan, Feiqian Zhu, Puneet Gupta, Ankur Mehta:
Cost-Driven Hardware-Software Co-Optimization of Machine Learning Pipelines. CoRR abs/2310.07940 (2023) - 2022
- [j2]Wojciech Romaszkan, Tianmu Li, Puneet Gupta:
SASCHA - Sparsity-Aware Stochastic Computing Hardware Architecture for Neural Network Acceleration. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(11): 4169-4180 (2022) - 2021
- [c2]Tianmu Li, Wojciech Romaszkan, Sudhakar Pamarti, Puneet Gupta:
GEO: Generation and Execution Optimized Stochastic Computing Accelerator for Neural Networks. DATE 2021: 689-694 - [i1]Shurui Li, Wojciech Romaszkan, Alexander Graening, Puneet Gupta:
SWIS - Shared Weight bIt Sparsity for Efficient Neural Network Acceleration. CoRR abs/2103.01308 (2021) - 2020
- [j1]Wojciech Romaszkan, Tianmu Li, Puneet Gupta:
3PXNet: Pruned-Permuted-Packed XNOR Networks for Edge Machine Learning. ACM Trans. Embed. Comput. Syst. 19(1): 5:1-5:23 (2020) - [c1]Wojciech Romaszkan, Tianmu Li, Tristan Melton, Sudhakar Pamarti, Puneet Gupta:
ACOUSTIC: Accelerating Convolutional Neural Networks through Or-Unipolar Skipped Stochastic Computing. DATE 2020: 768-773
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