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PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference.

A. Ankit, I. Hajj, S. Chalamalasetti, G. Ndu, M. Foltin, R. Williams, P. Faraboschi, W. mei W. Hwu, J. Strachan, K. Roy, and D. Milojicic. ASPLOS, page 715-731. ACM, (2019)

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Ankit Mittal

Ankit Goyal

Other publications of authors with the same name

In-Memory Computing in Emerging Memory Technologies for Machine Learning: An Overview.K. Roy, I. Chakraborty, M. Ali, A. Ankit, and A. Agrawal. DAC, page 1-6. IEEE, (2020)HyperX: A Hybrid RRAM-SRAM partitioned system for error recovery in memristive Xbars.A. Kosta, E. Soufleri, I. Chakraborty, A. Agrawal, A. Ankit, and K. Roy. DATE, page 88-91. IEEE, (2022)Resistive Crossbars as Approximate Hardware Building Blocks for Machine Learning: Opportunities and Challenges.I. Chakraborty, M. Ali, A. Ankit, S. Jain, S. Roy, S. Sridharan, A. Agrawal, A. Raghunathan, and K. Roy. Proc. IEEE, 108 (12): 2276-2310 (2020)Identifying Efficient Dataflows for Spiking Neural Networks.D. Sharma, A. Ankit, and K. Roy. ISLPED, page 2:1-2:6. ACM, (2022)NAX: neural architecture and memristive xbar based accelerator co-design.S. Negi, I. Chakraborty, A. Ankit, and K. Roy. DAC, page 451-456. ACM, (2022)RESPARC: A Reconfigurable and Energy-Efficient Architecture with Memristive Crossbars for Deep Spiking Neural Networks.A. Ankit, A. Sengupta, P. Panda, and K. Roy. DAC, page 27:1-27:6. ACM, (2017)Energy-Efficient Neural Computing with Approximate Multipliers.S. Sarwar, S. Venkataramani, A. Ankit, A. Raghunathan, and K. Roy. ACM J. Emerg. Technol. Comput. Syst., 14 (2): 16:1-16:23 (2018)TraNNsformer: Neural network transformation for memristive crossbar based neuromorphic system design.A. Ankit, A. Sengupta, and K. Roy. ICCAD, page 533-540. IEEE, (2017)Mixed Precision Quantization for ReRAM-based DNN Inference Accelerators.S. Huang, A. Ankit, P. Silveira, R. Antunes, S. Chalamalasetti, I. Hajj, D. Kim, G. Aguiar, P. Bruel, S. Serebryakov and 8 other author(s). ASP-DAC, page 372-377. ACM, (2021)PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference.A. Ankit, I. Hajj, S. Chalamalasetti, G. Ndu, M. Foltin, R. Williams, P. Faraboschi, W. mei W. Hwu, J. Strachan, K. Roy and 1 other author(s). ASPLOS, page 715-731. ACM, (2019)

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Disambiguation of "Ankit, Aayush"

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PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference.

Please choose a person to relate this publication to

Ankit Mittal

Ankit Goyal

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Ankit, Aayush"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference.

Please choose a person to relate this publication to

Ankit Mittal

Ankit Goyal

Other publications of authors with the same name

Disambiguation

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URL
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PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference.