default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDPrashant J. Nair
2020 – today
- 2025
[i16]Jeonghyun Woo, Prashant J. Nair:
DAPPER: A Performance-Attack-Resilient Tracker for RowHammer Defense. CoRR abs/2501.18857 (2025)- [i15]Jeonghyun Woo, Shaopeng Lin, Prashant J. Nair, Aamer Jaleel, Gururaj Saileshwar:
QPRAC: Towards Secure and Practical PRAC-based Rowhammer Mitigation using Priority Queues. CoRR abs/2501.18861 (2025) - 2024
- [c38]Meng Wang
, Bo Fang, Ang Li, Prashant J. Nair:
Red-QAOA: Efficient Variational Optimization through Circuit Reduction. ASPLOS (2) 2024: 980-998 - [c37]Bo Fang, Xinyi Li, Harvey Dam, Cheng Tan, Siva Kumar Sastry Hari, Timothy Tsai, Ignacio Laguna, Dingwen Tao, Ganesh Gopalakrishnan, Prashant J. Nair, Kevin J. Barker, Ang Li:
Understanding Mixed Precision GEMM with MPGemmFI: Insights into Fault Resilience. CLUSTER 2024: 166-178 - [c36]Muhammad Adnan, Yassaman Ebrahimzadeh Maboud, Divya Mahajan, Prashant J. Nair:
Heterogeneous Acceleration Pipeline for Recommendation System Training. ISCA 2024: 1063-1079 - [c35]Junhyeok Park, Osang Kwon, Yongho Lee, Seongwook Kim, Gwangeun Byeon, Jihun Yoon, Prashant J. Nair, Seokin Hong:
A Case for Speculative Address Translation with Rapid Validation for GPUs. MICRO 2024: 278-292 - [c34]Meng Wang, Poulami Das, Prashant J. Nair:
Qoncord: A Multi-Device Job Scheduling Framework for Variational Quantum Algorithms. MICRO 2024: 735-749 - [c33]Muhammad Adnan, Akhil Arunkumar, Gaurav Jain, Prashant J. Nair, Ilya Soloveychik, Purushotham Kamath:
Keyformer: KV Cache reduction through key tokens selection for Efficient Generative Inference. MLSys 2024 - [c32]Mushahid Khan, Prashant J. Nair, Olivia Di Matteo:
CircInspect: Integrating Visual Circuit Analysis, Abstraction, and Real-Time Development in Quantum Debugging. QCE 2024: 1000-1006 - [i14]Muhammad Adnan, Akhil Arunkumar, Gaurav Jain, Prashant J. Nair, Ilya Soloveychik, Purushotham Kamath:
Keyformer: KV Cache Reduction through Key Tokens Selection for Efficient Generative Inference. CoRR abs/2403.09054 (2024) - [i13]Yassaman Ebrahimzadeh Maboud, Muhammad Adnan, Divya Mahajan, Prashant J. Nair:
Accelerating Recommender Model Training by Dynamically Skipping Stale Embeddings. CoRR abs/2404.04270 (2024) - [i12]Muhammad Adnan, Amar Phanishayee, Janardhan Kulkarni, Prashant J. Nair, Divya Mahajan:
Workload-Aware Hardware Accelerator Mining for Distributed Deep Learning Training. CoRR abs/2404.14632 (2024) - 2023
- [c31]Gwangeun Byeon, Seungtae Lee, Seongwook Kim, Yongjun Kim, Prashant J. Nair, Seokin Hong:
SparseFT: Sparsity-aware Fault Tolerance for Reliable CNN Inference on GPUs. PACT 2023: 337-338 - [c30]Dingqing Yang, Prashant J. Nair, Mieszko Lis:
HuffDuff: Stealing Pruned DNNs from Sparse Accelerators. ASPLOS (2) 2023: 385-399 - [c29]Jeonghyun Woo, Gururaj Saileshwar, Prashant J. Nair:
Scalable and Secure Row-Swap: Efficient and Safe Row Hammer Mitigation in Memory Systems. HPCA 2023: 374-389 - [c28]Irene Wang, Prashant J. Nair, Divya Mahajan:
FLuID: Mitigating Stragglers in Federated Learning using Invariant Dropout. NeurIPS 2023 - [c27]Ali Asgari Khoshouyeh, Florian Geissler, Syed Sha Qutub, Michael Paulitsch, Prashant J. Nair, Karthik Pattabiraman:
Structural Coding: A Low-Cost Scheme to Protect CNNs from Large-Granularity Memory Faults. SC 2023: 85:1-85:17 - [c26]Meng Wang, Fei Hua, Chenxu Liu, Nicholas P. Bauman, Karol Kowalski, Daniel Claudino, Travis S. Humble, Prashant J. Nair, Ang Li:
Enabling Scalable VQE Simulation on Leading HPC Systems. SC Workshops 2023: 1460-1467 - [i11]Irene Wang, Prashant J. Nair, Divya Mahajan:
FLuID: Mitigating Stragglers in Federated Learning using Invariant Dropout. CoRR abs/2307.02623 (2023) - [i10]Muhammad Adnan, Yassaman Ebrahimzadeh Maboud, Divya Mahajan, Prashant J. Nair:
Ad-Rec: Advanced Feature Interactions to Address Covariate-Shifts in Recommendation Networks. CoRR abs/2308.14902 (2023) - [i9]Bo Fang, Xinyi Li, Harvey Dam, Cheng Tan, Siva Kumar Sastry Hari, Timothy Tsai, Ignacio Laguna, Dingwen Tao, Ganesh Gopalakrishnan, Prashant J. Nair, Kevin J. Barker, Ang Li:
MPGemmFI: A Fault Injection Technique for Mixed Precision GEMM in ML Applications. CoRR abs/2311.05782 (2023) - 2022
- [c25]Gururaj Saileshwar, Bolin Wang, Moinuddin K. Qureshi, Prashant J. Nair:
Randomized row-swap: mitigating Row Hammer by breaking spatial correlation between aggressor and victim rows. ASPLOS 2022: 1056-1069 - [c24]Ali Fakhrzadehgan, Yale N. Patt, Prashant J. Nair, Moinuddin K. Qureshi:
SafeGuard: Reducing the Security Risk from Row-Hammer via Low-Cost Integrity Protection. HPCA 2022: 373-386 - [c23]Moinuddin K. Qureshi, Aditya Rohan, Gururaj Saileshwar, Prashant J. Nair:
Hydra: enabling low-overhead mitigation of row-hammer at ultra-low thresholds via hybrid tracking. ISCA 2022: 699-710 - [c22]Anish Saxena, Gururaj Saileshwar, Prashant J. Nair, Moinuddin K. Qureshi:
AQUA: Scalable Rowhammer Mitigation by Quarantining Aggressor Rows at Runtime. MICRO 2022: 108-123 - [i8]Meng Wang, Rui Huang, Swamit S. Tannu, Prashant J. Nair:
TQSim: A Case for Reuse-Focused Tree-Based Quantum Circuit Simulation. CoRR abs/2203.13892 (2022) - [i7]Muhammad Adnan, Yassaman Ebrahimzadeh Maboud, Divya Mahajan, Prashant J. Nair:
Heterogeneous Acceleration Pipeline for Recommendation System Training. CoRR abs/2204.05436 (2022) - [i6]Swamit S. Tannu, Prashant J. Nair:
The Dirty Secret of SSDs: Embodied Carbon. CoRR abs/2207.10793 (2022) - [i5]Jeonghyun Woo, Gururaj Saileshwar, Prashant J. Nair:
Scalable and Secure Row-Swap: Efficient and Safe Row Hammer Mitigation in Memory Systems. CoRR abs/2212.12613 (2022) - 2021
- [j5]Muhammad Adnan, Yassaman Ebrahimzadeh Maboud, Divya Mahajan, Prashant J. Nair:
Accelerating Recommendation System Training by Leveraging Popular Choices. Proc. VLDB Endow. 15(1): 127-140 (2021) - [c21]Avilash Mukherjee, Kumar Saurav, Prashant J. Nair, Sudip Shekhar, Mieszko Lis:
A Case for Emerging Memories in DNN Accelerators. DATE 2021: 938-941 - [i4]Muhammad Adnan, Yassaman Ebrahimzadeh Maboud, Divya Mahajan, Prashant J. Nair:
High-Performance Training by Exploiting Hot-Embeddings in Recommendation Systems. CoRR abs/2103.00686 (2021) - 2020
- [c20]Amin Ghasemazar, Prashant J. Nair, Mieszko Lis:
Thesaurus: Efficient Cache Compression via Dynamic Clustering. ASPLOS 2020: 527-540 - [c19]Amin Ghasemazar, Mohammad Ewais, Prashant J. Nair, Mieszko Lis:
2DCC: Cache Compression in Two Dimensions. DATE 2020: 756-761 - [c18]Beomjun Kim, Prashant J. Nair, Seokin Hong:
ADAM: Adaptive Block Placement with Metadata Embedding for Hybrid Caches. ICCD 2020: 421-424
2010 – 2019
- 2019
- [c17]Prashant J. Nair, Bahar Asgari, Moinuddin K. Qureshi:
SuDoku: Tolerating High-Rate of Transient Failures for Enabling Scalable STTRAM. DSN 2019: 388-400 - [c16]Poulami Das, Swamit S. Tannu, Prashant J. Nair, Moinuddin K. Qureshi:
A Case for Multi-Programming Quantum Computers. MICRO 2019: 291-303 - [c15]Seokin Hong, Bülent Abali, Alper Buyuktosunoglu, Michael B. Healy, Prashant J. Nair:
Touché: Towards Ideal and Efficient Cache Compression By Mitigating Tag Area Overheads. MICRO 2019: 453-465 - [i3]Seokin Hong, Bülent Abali, Alper Buyuktosunoglu, Michael B. Healy, Prashant J. Nair:
Touché: Towards Ideal and Efficient Cache Compression By Mitigating Tag Area Overheads. CoRR abs/1909.00553 (2019) - 2018
- [c14]Gururaj Saileshwar, Prashant J. Nair, Prakash Ramrakhyani, Wendy Elsasser, Moinuddin K. Qureshi:
SYNERGY: Rethinking Secure-Memory Design for Error-Correcting Memories. HPCA 2018: 454-465 - [c13]Seokin Hong, Prashant Jayaprakash Nair, Bülent Abali, Alper Buyuktosunoglu, Kyu-Hyoun Kim, Michael B. Healy:
Attaché: Towards Ideal Memory Compression by Mitigating Metadata Bandwidth Overheads. MICRO 2018: 326-338 - [c12]Gururaj Saileshwar, Prashant J. Nair, Prakash Ramrakhyani, Wendy Elsasser, José A. Joao, Moinuddin K. Qureshi:
Morphable Counters: Enabling Compact Integrity Trees For Low-Overhead Secure Memories. MICRO 2018: 416-427 - [i2]Kevin K. Chang, Prashant J. Nair, Saugata Ghose, Donghyuk Lee, Moinuddin K. Qureshi, Onur Mutlu:
LISA: Increasing Internal Connectivity in DRAM for Fast Data Movement and Low Latency. CoRR abs/1805.03184 (2018) - 2017
- [b1]Prashant J. Nair:
Architectural techniques to enable reliable and scalable memory systems. Georgia Institute of Technology, Atlanta, GA, USA, 2017 - [c11]Vinson Young, Prashant J. Nair, Moinuddin K. Qureshi:
DICE: Compressing DRAM Caches for Bandwidth and Capacity. ISCA 2017: 627-638 - [c10]Swamit S. Tannu, Zachary A. Myers, Prashant J. Nair, Douglas M. Carmean, Moinuddin K. Qureshi:
Taming the instruction bandwidth of quantum computers via hardware-managed error correction. MICRO 2017: 679-691 - [i1]Prashant J. Nair:
Architectural Techniques to Enable Reliable and Scalable Memory Systems. CoRR abs/1704.03991 (2017) - 2016
- [j4]Prashant J. Nair, David A. Roberts, Moinuddin K. Qureshi:
FaultSim: A Fast, Configurable Memory-Reliability Simulator for Conventional and 3D-Stacked Systems. ACM Trans. Archit. Code Optim. 12(4): 44:1-44:24 (2016) - [j3]Prashant J. Nair, David A. Roberts, Moinuddin K. Qureshi:
Citadel: Efficiently Protecting Stacked Memory from TSV and Large Granularity Failures. ACM Trans. Archit. Code Optim. 12(4): 49:1-49:24 (2016) - [c9]Kevin K. Chang, Prashant J. Nair, Donghyuk Lee, Saugata Ghose, Moinuddin K. Qureshi, Onur Mutlu:
Low-Cost Inter-Linked Subarrays (LISA): Enabling fast inter-subarray data movement in DRAM. HPCA 2016: 568-580 - [c8]Prashant J. Nair, Vilas Sridharan, Moinuddin K. Qureshi:
XED: Exposing On-Die Error Detection Information for Strong Memory Reliability. ISCA 2016: 341-353 - 2015
- [j2]Dae-Hyun Kim, Prashant J. Nair, Moinuddin K. Qureshi:
Architectural Support for Mitigating Row Hammering in DRAM Memories. IEEE Comput. Archit. Lett. 14(1): 9-12 (2015) - [c7]Vinson Young, Prashant J. Nair, Moinuddin K. Qureshi:
DEUCE: Write-Efficient Encryption for Non-Volatile Memories. ASPLOS 2015: 33-44 - [c6]Chia-Chen Chou, Prashant J. Nair, Moinuddin K. Qureshi:
Reducing Refresh Power in Mobile Devices with Morphable ECC. DSN 2015: 355-366 - [c5]Moinuddin K. Qureshi, Dae-Hyun Kim, Samira Manabi Khan, Prashant J. Nair, Onur Mutlu:
AVATAR: A Variable-Retention-Time (VRT) Aware Refresh for DRAM Systems. DSN 2015: 427-437 - [c4]Prashant J. Nair, Chia-Chen Chou, Bipin Rajendran, Moinuddin K. Qureshi:
Reducing read latency of phase change memory via early read and Turbo Read. HPCA 2015: 309-319 - 2014
- [j1]Prashant J. Nair, Chia-Chen Chou, Moinuddin K. Qureshi:
Refresh pausing in DRAM memory systems. ACM Trans. Archit. Code Optim. 11(1): 10:1-10:26 (2014) - [c3]Prashant J. Nair, David A. Roberts, Moinuddin K. Qureshi:
Citadel: Efficiently Protecting Stacked Memory from Large Granularity Failures. MICRO 2014: 51-62 - 2013
- [c2]Prashant J. Nair, Chia-Chen Chou, Moinuddin K. Qureshi:
A case for Refresh Pausing in DRAM memory systems. HPCA 2013: 627-638 - [c1]Prashant J. Nair, Dae-Hyun Kim, Moinuddin K. Qureshi:
ArchShield: architectural framework for assisting DRAM scaling by tolerating high error rates. ISCA 2013: 72-83
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
[+][–] Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
[+][–] Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-03-04 21:17 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
