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Nishil Talati
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Publications
- 2023
- [j5]Yichao Yuan, Haojie Ye, Sanketh Vedula, Wynn Kaza, Nishil Talati:
Everest: GPU-Accelerated System For Mining Temporal Motifs. Proc. VLDB Endow. 17(2): 162-174 (2023) - [j4]Yuhan Chen, Haojie Ye, Sanketh Vedula, Alex M. Bronstein, Ronald G. Dreslinski, Trevor N. Mudge, Nishil Talati:
Demystifying Graph Sparsification Algorithms in Graph Properties Preservation. Proc. VLDB Endow. 17(3): 427-440 (2023) - [c15]Haojie Ye, Sanketh Vedula, Yuhan Chen, Yichen Yang, Alex M. Bronstein, Ronald G. Dreslinski, Trevor N. Mudge, Nishil Talati:
GRACE: A Scalable Graph-Based Approach to Accelerating Recommendation Model Inference. ASPLOS (3) 2023: 282-301 - [c14]Yuhan Chen, Alireza Khadem, Xin He, Nishil Talati, Tanvir Ahmed Khan, Trevor N. Mudge:
PEDAL: A Power Efficient GCN Accelerator with Multiple DAtafLows. DATE 2023: 1-6 - [c13]Alireza Khadem, Daichi Fujiki, Nishil Talati, Scott A. Mahlke, Reetuparna Das:
Vector-Processing for Mobile Devices: Benchmark and Analysis. IISWC 2023: 15-27 - [c12]Heewoo Kim, Haojie Ye, Trevor N. Mudge, Ronald G. Dreslinski, Nishil Talati:
RecPIM: A PIM-Enabled DRAM-RRAM Hybrid Memory System For Recommendation Models. ISLPED 2023: 1-6 - [i4]Yichen Yang, Jingtao Li, Nishil Talati, Subhankar Pal, Siying Feng, Chaitali Chakrabarti, Trevor N. Mudge, Ronald G. Dreslinski:
Accelerating Graph Analytics on a Reconfigurable Architecture with a Data-Indirect Prefetcher. CoRR abs/2301.12312 (2023) - [i3]Alireza Khadem, Daichi Fujiki, Nishil Talati, Scott A. Mahlke, Reetuparna Das:
Vector-Processing for Mobile Devices: Benchmark and Analysis. CoRR abs/2309.02680 (2023) - [i2]Yichao Yuan, Haojie Ye, Sanketh Vedula, Wynn Kaza, Nishil Talati:
Everest: GPU-Accelerated System For Mining Temporal Motifs. CoRR abs/2310.02800 (2023) - [i1]Yuhan Chen, Haojie Ye, Sanketh Vedula, Alex M. Bronstein, Ronald G. Dreslinski, Trevor N. Mudge, Nishil Talati:
Demystifying Graph Sparsification Algorithms in Graph Properties Preservation. CoRR abs/2311.12314 (2023) - 2022
- [c11]Leul Belayneh, Haojie Ye, Kuan-Yu Chen, David T. Blaauw, Trevor N. Mudge, Ronald G. Dreslinski, Nishil Talati:
Locality-Aware Optimizations for Improving Remote Memory Latency in Multi-GPU Systems. PACT 2022: 304-316 - [c10]Nishil Talati, Haojie Ye, Yichen Yang, Leul Belayneh, Kuan-Yu Chen, David T. Blaauw, Trevor N. Mudge, Ronald G. Dreslinski:
NDMiner: accelerating graph pattern mining using near data processing. ISCA 2022: 146-159 - [c9]Nishil Talati, Haojie Ye, Sanketh Vedula, Kuan-Yu Chen, Yuhan Chen, Daniel Liu, Yichao Yuan, David T. Blaauw, Alex M. Bronstein, Trevor N. Mudge, Ronald G. Dreslinski:
Mint: An Accelerator For Mining Temporal Motifs. MICRO 2022: 1270-1287 - 2021
- [j3]Heewoo Kim, Aporva Amarnath, Javad Bagherzadeh, Nishil Talati, Ronald G. Dreslinski:
A Survey Describing Beyond Si Transistors and Exploring Their Implications for Future Processors. ACM J. Emerg. Technol. Comput. Syst. 17(3): 27:1-27:44 (2021) - [c8]Nishil Talati, Kyle May, Armand Behroozi, Yichen Yang, Kuba Kaszyk, Christos Vasiladiotis, Tarunesh Verma, Lu Li, Brandon Nguyen, Jiawen Sun, John Magnus Morton, Agreen Ahmadi, Todd M. Austin, Michael F. P. O'Boyle, Scott A. Mahlke, Trevor N. Mudge, Ronald G. Dreslinski:
Prodigy: Improving the Memory Latency of Data-Indirect Irregular Workloads Using Hardware-Software Co-Design. HPCA 2021: 654-667 - [c7]Nishil Talati, Di Jin, Haojie Ye, Ajay Brahmakshatriya, Ganesh S. Dasika, Saman P. Amarasinghe, Trevor N. Mudge, Danai Koutra, Ronald G. Dreslinski:
A Deep Dive Into Understanding The Random Walk-Based Temporal Graph Learning. IISWC 2021: 87-100 - 2020
- [c6]Yichen Yang, Haojie Ye, Yuhan Chen, Xueyang Liu, Nishil Talati, Xin He, Trevor N. Mudge, Ronald G. Dreslinski:
CoPTA: Contiguous Pattern Speculating TLB Architecture. SAMOS 2020: 67-83
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