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Saransh Gupta
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2020 – today
- 2024
- [j10]Saransh Gupta
, Rosario Cammarota
MemFHE: End-to-end Computing with Fully Homomorphic Encryption in Memory. ACM Trans. Embed. Comput. Syst. 23(2): 28:1-28:23 (2024) - 2023
- [j9]Jeffrey Wang, Joao Souza de Vale, Saransh Gupta, Pulakesh Upadhyaya, Felipe A. Lisboa, Seth A. Schobel
ClotCatcher: a novel natural language model to accurately adjudicate venous thromboembolism from radiology reports. BMC Medical Informatics Decis. Mak. 23(1): 262 (2023) - [j8]Weihong Xu
RAPIDx: High-Performance ReRAM Processing In-Memory Accelerator for Sequence Alignment. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(10): 3275-3288 (2023) - [c35]Subham Panda, Rishik Gupta, Chandan Kumar, Rashi Mishra, Saransh Gupta, Akash Bhardwaj, Pratiksh Kumar, Prakhar Shukla, Bagesh Kumar:
Enhanced Heart Disease Classification Using Parallelization and Integrated Machine-Learning Techniques. CVIP (3) 2023: 411-422 - [c34]Yujin Nam, Minxuan Zhou, Saransh Gupta, Gabrielle De Micheli, Rosario Cammarota, Chris Wilkerson, Daniele Micciancio, Tajana Rosing:
Efficient Machine Learning on Encrypted Data Using Hyperdimensional Computing. ISLPED 2023: 1-6 - [c33]Hanning Chen, Yeseong Kim, Elaheh Sadredini, Saransh Gupta, Hugo Latapie, Mohsen Imani:
Sparsity Controllable Hyperdimensional Computing for Genome Sequence Matching Acceleration. VLSI-SoC 2023: 1-6 - [i6]Minxuan Zhou, Yujin Nam, Pranav Gangwar, Weihong Xu, Arpan Dutta, Kartikeyan Subramanyam, Chris Wilkerson, Rosario Cammarota, Saransh Gupta, Tajana Rosing:
FHEmem: A Processing In-Memory Accelerator for Fully Homomorphic Encryption. CoRR abs/2311.16293 (2023) - 2022
- [j7]Saransh Gupta
COSMO: Computing with Stochastic Numbers in Memory. ACM J. Emerg. Technol. Comput. Syst. 18(2): 37:1-37:25 (2022) - [j6]Saransh Gupta
Store-n-Learn: Classification and Clustering with Hyperdimensional Computing across Flash Hierarchy. ACM Trans. Embed. Comput. Syst. 21(3): 22:1-22:25 (2022) - [j5]Saransh Gupta
Integrative Network Modeling Highlights the Crucial Roles of Rho-GDI Signaling Pathway in the Progression of non-Small Cell Lung Cancer. IEEE J. Biomed. Health Informatics 26(9): 4785-4793 (2022) - [c32]Arpan Dutta, Saransh Gupta, Behnam Khaleghi, Rishikanth Chandrasekaran, Weihong Xu, Tajana Rosing:
HDnn-PIM: Efficient in Memory Design of Hyperdimensional Computing with Feature Extraction. ACM Great Lakes Symposium on VLSI 2022: 281-286 - [i5]Saransh Gupta, Rosario Cammarota, Tajana Rosing:
MemFHE: End-to-End Computing with Fully Homomorphic Encryption in Memory. CoRR abs/2204.12557 (2022) - [i4]Weihong Xu, Saransh Gupta, Niema Moshiri, Tajana Rosing:
RAPIDx: High-performance ReRAM Processing in-Memory Accelerator for Sequence Alignment. CoRR abs/2211.05733 (2022) - 2021
- [b1]Saransh Gupta:
Efficient and Secure Learning across Memory Hierarchy. University of California, San Diego, USA, 2021 - [c31]Minxuan Zhou, Guoyang Chen, Mohsen Imani, Saransh Gupta, Weifeng Zhang, Tajana Rosing:
PIM-DL: Boosting DNN Inference on Digital Processing In-Memory Architectures via Data Layout Optimizations. PACT 2021: 1 - [c30]Minxuan Zhou, Mohsen Imani, Yeseong Kim, Saransh Gupta, Tajana Rosing:
DP-Sim: A Full-stack Simulation Infrastructure for Digital Processing In-Memory Architectures. ASP-DAC 2021: 639-644 - [c29]Saransh Gupta, Tajana Simunic Rosing:
Invited: Accelerating Fully Homomorphic Encryption with Processing in Memory. DAC 2021: 1335-1338 - [c28]Yeseong Kim, Mohsen Imani, Saransh Gupta, Minxuan Zhou, Tajana Simunic Rosing:
Massively Parallel Big Data Classification on a Programmable Processing In-Memory Architecture. ICCAD 2021: 1-9 - [c27]Yilun Hao, Saransh Gupta, Justin Morris
Stochastic-HD: Leveraging Stochastic Computing on Hyper-Dimensional Computing. ICCD 2021: 321-325 - 2020
- [j4]Mohsen Imani
SearcHD: A Memory-Centric Hyperdimensional Computing With Stochastic Training. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(10): 2422-2433 (2020) - [c26]Hamid Nejatollahi, Saransh Gupta, Mohsen Imani, Tajana Simunic Rosing, Rosario Cammarota, Nikil D. Dutt
CryptoPIM: In-memory Acceleration for Lattice-based Cryptographic Hardware. DAC 2020: 1-6 - [c25]Saransh Gupta, Mohsen Imani, Joonseop Sim, Andrew Huang, Fan Wu, M. Hassan Najafi, Tajana Rosing:
SCRIMP: A General Stochastic Computing Architecture using ReRAM in-Memory Processing. DATE 2020: 1598-1601 - [c24]Mohsen Imani, Mohammad Samragh Razlighi, Yeseong Kim, Saransh Gupta, Farinaz Koushanfar
Deep Learning Acceleration with Neuron-to-Memory Transformation. HPCA 2020: 1-14 - [c23]Saransh Gupta, Justin Morris
THRIFTY: Training with Hyperdimensional Computing across Flash Hierarchy. ICCAD 2020: 27:1-27:9 - [c22]Saransh Gupta, Mohsen Imani, Hengyu Zhao, Fan Wu, Jishen Zhao, Tajana Simunic Rosing:
Implementing binary neural networks in memory with approximate accumulation. ISLPED 2020: 247-252 - [c21]Mohsen Imani, Saikishan Pampana, Saransh Gupta, Minxuan Zhou, Yeseong Kim, Tajana Rosing:
DUAL: Acceleration of Clustering Algorithms using Digital-based Processing In-Memory. MICRO 2020: 356-371 - [c20]Mohsen Imani, Saransh Gupta, Yeseong Kim, Tajana Rosing:
Deep Learning Acceleration using Digital-Based Processing In-Memory. SoCC 2020: 123-128 - [c19]Justin Morris
Multi-label HD Classification in 3D Flash. VLSI-SOC 2020: 10-15 - [i3]Rosario Cammarota, Matthias Schunter, Anand Rajan, Fabian Boemer, Ágnes Kiss, Amos Treiber, Christian Weinert, Thomas Schneider, Emmanuel Stapf, Ahmad-Reza Sadeghi, Daniel Demmler
Trustworthy AI Inference Systems: An Industry Research View. CoRR abs/2008.04449 (2020) - [i2]Hamid Nejatollahi, Saransh Gupta, Mohsen Imani, Tajana Simunic Rosing, Rosario Cammarota, Nikil D. Dutt:
CryptoPIM: In-memory Acceleration for Lattice-based Cryptographic Hardware. IACR Cryptol. ePrint Arch. 2020: 276 (2020)
2010 – 2019
- 2019
- [j3]Mohsen Imani
Hardware-Software Co-design to Accelerate Neural Network Applications. ACM J. Emerg. Technol. Comput. Syst. 15(2): 21:1-21:18 (2019) - [j2]Saransh Gupta
NNPIM: A Processing In-Memory Architecture for Neural Network Acceleration. IEEE Trans. Computers 68(9): 1325-1337 (2019) - [j1]Mohsen Imani
NVQuery: Efficient Query Processing in Nonvolatile Memory. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 38(4): 628-639 (2019) - [c18]Mohsen Imani, Sahand Salamat, Saransh Gupta
FACH: FPGA-based acceleration of hyperdimensional computing by reducing computational complexity. ASP-DAC 2019: 493-498 - [c17]Minxuan Zhou, Mohsen Imani, Saransh Gupta
GRAM: graph processing in a ReRAM-based computational memory. ASP-DAC 2019: 591-596 - [c16]Minxuan Zhou, Mohsen Imani, Saransh Gupta, Tajana Rosing:
Thermal-Aware Design and Management for Search-based In-Memory Acceleration. DAC 2019: 174 - [c15]Mohsen Imani, Yeseong Kim, Thomas Worley, Saransh Gupta, Tajana Rosing:
HDCluster: An Accurate Clustering Using Brain-Inspired High-Dimensional Computing. DATE 2019: 1591-1594 - [c14]Saransh Gupta, Mohsen Imani, Tajana Rosing:
Exploring Processing In-Memory for Different Technologies. ACM Great Lakes Symposium on VLSI 2019: 201-206 - [c13]Joonseop Sim, Saransh Gupta, Mohsen Imani, Yeseong Kim, Tajana Rosing:
UPIM: Unipolar Switching Logic for High Density Processing-in-Memory Applications. ACM Great Lakes Symposium on VLSI 2019: 255-258 - [c12]Mohsen Imani, Saransh Gupta, Yeseong Kim, Minxuan Zhou, Tajana Rosing:
DigitalPIM: Digital-based Processing In-Memory for Big Data Acceleration. ACM Great Lakes Symposium on VLSI 2019: 429-434 - [c11]Mohsen Imani, Saransh Gupta, Yeseong Kim, Tajana Rosing:
FloatPIM: in-memory acceleration of deep neural network training with high precision. ISCA 2019: 802-815 - [c10]Saransh Gupta, Mohsen Imani, Behnam Khaleghi, Venkatesh Kumar, Tajana Rosing:
RAPID: A ReRAM Processing in-Memory Architecture for DNA Sequence Alignment. ISLPED 2019: 1-6 - [c9]Joonseop Sim, Minsu Kim, Yeseong Kim, Saransh Gupta, Behnam Khaleghi, Tajana Rosing:
MAPIM: Mat Parallelism for High Performance Processing in Non-volatile Memory Architecture. ISQED 2019: 145-150 - [c8]Mohsen Imani, Saransh Gupta, Tajana Rosing:
Digital-based processing in-memory: a highly-parallel accelerator for data intensive applications. MEMSYS 2019: 38-40 - 2018
- [c7]Mohsen Imani, Saransh Gupta
GenPIM: Generalized processing in-memory to accelerate data intensive applications. DATE 2018: 1155-1158 - [c6]Saransh Gupta
FELIX: fast and energy-efficient logic in memory. ICCAD 2018: 55 - [c5]Sahand Salamat, Mohsen Imani, Saransh Gupta
RNSnet: In-Memory Neural Network Acceleration Using Residue Number System. ICRC 2018: 1-12 - [c4]Mohsen Imani, Ricardo Garcia, Saransh Gupta
RMAC: Runtime Configurable Floating Point Multiplier for Approximate Computing. ISLPED 2018: 12:1-12:6 - [c3]Minxuan Zhou, Mohsen Imani, Saransh Gupta
GAS: A Heterogeneous Memory Architecture for Graph Processing. ISLPED 2018: 27:1-27:6 - [i1]Mohsen Imani, Mohammad Samragh, Yeseong Kim, Saransh Gupta, Farinaz Koushanfar, Tajana Rosing:
RAPIDNN: In-Memory Deep Neural Network Acceleration Framework. CoRR abs/1806.05794 (2018) - 2017
- [c2]Mohsen Imani, Saransh Gupta
Ultra-Efficient Processing In-Memory for Data Intensive Applications. DAC 2017: 6:1-6:6 - [c1]Mohsen Imani, Saransh Gupta
Efficient query processing in crossbar memory. ISLPED 2017: 1-6
Coauthor Index
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last updated on 2024-11-11 21:29 CET by the dblp team
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