![](https://dblp.org/img/logo.ua.320x120.png)
![](https://dblp.org/img/dropdown.dark.16x16.png)
![](https://dblp.org/img/peace.dark.16x16.png)
Остановите войну!
for scientists:
![search dblp search dblp](https://dblp.org/img/search.dark.16x16.png)
![search dblp](https://dblp.org/img/search.dark.16x16.png)
default search action
Sparsh Mittal
Person information
Refine list
![note](https://dblp.org/img/note-mark.dark.12x12.png)
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [c44]Maruthi Seshidhar Inukonda, Krishna Prashanth Thummanapelly, Bheemarjuna Reddy Tamma, Sparsh Mittal:
TEFAR: An Efficient Transparent Finer-Grained Encryption of Internet Access Artifacts. COMSNETS 2024: 1164-1169 - [c43]Vishesh Mishra
, Sparsh Mittal, Nirbhay Mishra, Rekha Singhal:
Security Implications of Approximation: A Study of Trojan Attacks on Approximate Adders and Multipliers. VLSID 2024: 511-516 - [c42]Gayatri Deshmukh, Onkar Susladkar, Dhruv Makwana, Sparsh Mittal, R. Sai Chandra Teja:
Textual Alchemy: CoFormer for Scene Text Understanding. WACV 2024: 2919-2929 - [c41]Dhruv Makwana, Gayatri Deshmukh, Onkar Susladkar, Sparsh Mittal, R. Sai Chandra Teja:
LIVENet: A novel network for real-world low-light image denoising and enhancement. WACV 2024: 5844-5853 - [c40]Vandan Gorade, Sparsh Mittal, Debesh Jha, Ulas Bagci:
SynergyNet: Bridging the Gap between Discrete and Continuous Representations for Precise Medical Image Segmentation. WACV 2024: 7753-7762 - [i29]Vandan Gorade, Sparsh Mittal, Debesh Jha, Rekha Singhal, Ulas Bagci:
Harmonized Spatial and Spectral Learning for Robust and Generalized Medical Image Segmentation. CoRR abs/2401.10373 (2024) - 2023
- [j74]Vandan Gorade
, Sparsh Mittal
, Rekha Singhal:
PaCL: Patient-aware contrastive learning through metadata refinement for generalized early disease diagnosis. Comput. Biol. Medicine 167: 107569 (2023) - [j73]Dhruv Makwana
, R. Sai Chandra Teja
, Sparsh Mittal
:
PCBSegClassNet - A light-weight network for segmentation and classification of PCB component. Expert Syst. Appl. 225: 120029 (2023) - [j72]Aabid Amin Fida, Farooq Ahmad Khanday, Sparsh Mittal
:
An active memristor based rate-coded spiking neural network. Neurocomputing 533: 61-71 (2023) - [j71]Krishna Teja Chitty-Venkata, Sparsh Mittal
, Murali Emani, Venkatram Vishwanath, Arun K. Somani:
A survey of techniques for optimizing transformer inference. J. Syst. Archit. 144: 102990 (2023) - [j70]Jens Domke
, Emil Vatai
, Balazs Gerofi
, Yuetsu Kodama
, Mohamed Wahib
, Artur Podobas
, Sparsh Mittal
, Miquel Pericàs
, Lingqi Zhang
, Peng Chen
, Aleksandr Drozd
, Satoshi Matsuoka
:
At the Locus of Performance: Quantifying the Effects of Copious 3D-Stacked Cache on HPC Workloads. ACM Trans. Archit. Code Optim. 20(4): 57:1-57:26 (2023) - [j69]Vishesh Mishra
, Sparsh Mittal
, Neelofar Hassan
, Rekha Singhal
, Urbi Chatterjee
:
VADF: Versatile Approximate Data Formats for Energy-Efficient Computing. ACM Trans. Embed. Comput. Syst. 22(5s): 111:1-111:21 (2023) - [j68]Sparsh Mittal
, Srishti Srivastava
, J. Phani Jayanth
:
A Survey of Deep Learning Techniques for Underwater Image Classification. IEEE Trans. Neural Networks Learn. Syst. 34(10): 6968-6982 (2023) - [c39]Maruthi Seshidhar Inukonda, Jatin Tarachandani, Imtiaz Ahmed, Bheemarjuna Reddy Tamma, Sparsh Mittal:
ZETA: A Zero-Trust Security based Forensic-Ready Solution for Perimeter-less Enterprise Networks. ANTS 2023: 189-194 - [c38]Onkar Susladkar
, Gayatri S. Deshmukh
, Sparsh Mittal
, R. Sai Chandra Teja
, Rekha Singhal
:
LiBERTy: A Novel Model for Natural Language Understanding. AIMLSystems 2023: 1:1-1:9 - [c37]Aaditi Kapre, Shruti Kunde, Sparsh Mittal, Rekha Singhal:
RAxC: Reflexivity-based Approximate Computing techniques for efficient remote sensing. IEEE Big Data 2023: 1168-1173 - [c36]Maruthi Seshidhar Inukonda, Sai Harsha Kottapalli, Bheemarjuna Reddy Tamma, Sparsh Mittal:
FENCE: A Real-Time Privacy-Preserving Solution for Enterprise Internet Forensics at Scale. COMSNETS 2023: 174-176 - [c35]Onkar Susladkar
, Dhruv Makwana
, Gayatri Deshmukh
, Sparsh Mittal
, R. Sai Chandra Teja
, Rekha Singhal
:
TPFNet: A Novel Text In-painting Transformer for Text Removal. ICDAR (6) 2023: 155-172 - [c34]Yash Khare, Kumud Lakara, Sparsh Mittal, Arvind Kaushik, Rekha Singhal:
SpotOn: A Gradient-based Targeted Data Poisoning Attack on Deep Neural Networks. ISQED 2023: 1-8 - [c33]Ananya Mantravadi, Dhruv Makwana
, R. Sai Chandra Teja, Sparsh Mittal, Rekha Singhal:
Dilated Involutional Pyramid Network (DInPNet): A Novel Model for Printed Circuit Board (PCB) Components Classification. ISQED 2023: 1-7 - [c32]Vishesh Mishra
, Sparsh Mittal, Rekha Singhal, Manoj Nambiar:
Novel, Configurable Approximate Floating-point Multipliers for Error-Resilient Applications. ISQED 2023: 1-7 - [c31]Vishu Saxena, Yash Jain, Sparsh Mittal:
Machine Learning and Polynomial Chaos models for Accurate Prediction of SET Pulse Current. ISVLSI 2023: 1-6 - [c30]Vibhu
, Sparsh Mittal, Vivek Kumar
:
Machine Learning-based model for Single Event Upset Current Prediction in 14nm FinFETs. VLSID 2023: 1-6 - [c29]Onkar Susladkar, Gayatri Deshmukh, Dhruv Makwana
, Sparsh Mittal, R. Sai Chandra Teja, Rekha Singhal:
GAFNet: A Global Fourier Self Attention Based Novel Network for multi-modal downstream tasks. WACV 2023: 5231-5240 - [i28]Krishna Teja Chitty-Venkata, Sparsh Mittal, Murali Emani, Venkatram Vishwanath, Arun K. Somani:
A Survey of Techniques for Optimizing Transformer Inference. CoRR abs/2307.07982 (2023) - [i27]Vandan Gorade, Sparsh Mittal, Debesh Jha, Ulas Bagci:
SynergyNet: Bridging the Gap between Discrete and Continuous Representations for Precise Medical Image Segmentation. CoRR abs/2310.17764 (2023) - [i26]Vandan Gorade, Sparsh Mittal, Debesh Jha, Ulas Bagci:
Rethinking Intermediate Layers design in Knowledge Distillation for Kidney and Liver Tumor Segmentation. CoRR abs/2311.16700 (2023) - [i25]Tushir Sahu
, Vidhi Bhatt, R. Sai Chandra Teja, Sparsh Mittal, Nagesh Kumar S:
SPEEDNet: Salient Pyramidal Enhancement Encoder-Decoder Network for Colonoscopy Images. CoRR abs/2312.01128 (2023) - 2022
- [j67]Maruthi Seshidhar Inukonda
, Atharva Rajendra Karpate, Bheemarjuna Reddy Tamma
, Sparsh Mittal
, Praveen Tammana
:
NASCENT: A Non-Invasive Solution for Detecting Utilization of Servers in Bare-Metal Cloud. IEEE Access 10: 12866-12881 (2022) - [j66]Subhrajit Nag, Dhruv Makwana
, R. Sai Chandra Teja
, Sparsh Mittal, C. Krishna Mohan:
WaferSegClassNet - A light-weight network for classification and segmentation of semiconductor wafer defects. Comput. Ind. 142: 103720 (2022) - [j65]Onkar Susladkar, Gayatri Deshmukh
, Subhrajit Nag, Ananya Mantravadi, Dhruv Makwana
, Sujitha Ravichandran, R. Sai Chandra Teja, Gajanan H. Chavhan
, C. Krishna Mohan, Sparsh Mittal
:
ClarifyNet: A high-pass and low-pass filtering based CNN for single image dehazing. J. Syst. Archit. 132: 102736 (2022) - [j64]Sheel Sindhu Manohar, Sparsh Mittal
, Hemangee K. Kapoor:
CORIDOR: Using COherence and TempoRal LocalIty to Mitigate Read Disurbance ErrOR in STT-RAM Caches. ACM Trans. Embed. Comput. Syst. 21(1): 2:1-2:24 (2022) - [j63]Sparsh Mittal
, Poonam Rajput, Sreenivas Subramoney:
A Survey of Deep Learning on CPUs: Opportunities and Co-Optimizations. IEEE Trans. Neural Networks Learn. Syst. 33(10): 5095-5115 (2022) - [c28]Yash Jain
, Vishu Saxena
, Sparsh Mittal
:
Ensembling Deep Learning And CIELAB Color Space Model for Fire Detection from UAV images. AIMLSystems 2022: 7:1-7:9 - [c27]Yash Khare, Kumud Lakara, Maruthi Seshidhar Inukonda, Sparsh Mittal, Mahesh Chandra, Arvind Kaushik:
Design and Analysis of Novel Bit-flip Attacks and Defense Strategies for DNNs. DSC 2022: 1-8 - [c26]Sudhir Kumar Rai, Ashish Mittal, Sparsh Mittal:
A Node-Embedding Features Based Machine Learning Technique for Dynamic Malware Detection. DSC 2022: 1-8 - [c25]Vishesh Mishra
, Sparsh Mittal, Saurabh Singh
, Divy Pandey, Rekha Singhal:
MEGA-MAC: A Merged Accumulation based Approximate MAC Unit for Error Resilient Applications. ACM Great Lakes Symposium on VLSI 2022: 325-328 - [i24]Jens Domke, Emil Vatai, Balazs Gerofi, Yuetsu Kodama, Mohamed Wahib, Artur Podobas, Sparsh Mittal, Miquel Pericàs, Lingqi Zhang, Peng Chen, Aleksandr Drozd, Satoshi Matsuoka:
At the Locus of Performance: A Case Study in Enhancing CPUs with Copious 3D-Stacked Cache. CoRR abs/2204.02235 (2022) - [i23]Subhrajit Nag, Dhruv Makwana
, R. Sai Chandra Teja, Sparsh Mittal, C. Krishna Mohan:
WaferSegClassNet - A Light-weight Network for Classification and Segmentation of Semiconductor Wafer Defects. CoRR abs/2207.00960 (2022) - [i22]Dhruv Makwana
, Subhrajit Nag, Onkar Susladkar, Gayatri Deshmukh, R. Sai Chandra Teja, Sparsh Mittal, C. Krishna Mohan:
ACLNet: An Attention and Clustering-based Cloud Segmentation Network. CoRR abs/2207.06277 (2022) - [i21]Onkar Susladkar, Dhruv Makwana
, Gayatri Deshmukh, Sparsh Mittal, R. Sai Chandra Teja, Rekha Singhal:
TPFNet: A Novel Text In-painting Transformer for Text Removal. CoRR abs/2210.14461 (2022) - 2021
- [j62]Sparsh Mittal, Sumanth Umesh
:
A survey On hardware accelerators and optimization techniques for RNNs. J. Syst. Archit. 112: 101839 (2021) - [j61]Sumanth Umesh
, Sparsh Mittal
:
A survey of techniques for intermittent computing. J. Syst. Archit. 112: 101859 (2021) - [j60]Sparsh Mittal
, Vibhu
:
A survey of accelerator architectures for 3D convolution neural networks. J. Syst. Archit. 115: 102041 (2021) - [j59]Santanu Pattanayak, Subhrajit Nag, Sparsh Mittal
:
CURATING: A multi-objective based pruning technique for CNNs. J. Syst. Archit. 116: 102031 (2021) - [j58]Srishti Srivastava
, Sarthak Narayan, Sparsh Mittal
:
A survey of deep learning techniques for vehicle detection from UAV images. J. Syst. Archit. 117: 102152 (2021) - [j57]Sparsh Mittal
, Himanshi Gupta
, Srishti Srivastava
:
A survey on hardware security of DNN models and accelerators. J. Syst. Archit. 117: 102163 (2021) - [j56]Nivedita Shrivastava, Muhammad Abdullah Hanif, Sparsh Mittal
, Smruti Ranjan Sarangi
, Muhammad Shafique
:
A survey of hardware architectures for generative adversarial networks. J. Syst. Archit. 118: 102227 (2021) - [j55]Sparsh Mittal
, Gaurav Verma
, Brajesh Kumar Kaushik
, Farooq Ahmad Khanday
:
A survey of SRAM-based in-memory computing techniques and applications. J. Syst. Archit. 119: 102276 (2021) - [j54]Nandan Kumar Jha
, Sparsh Mittal
:
Modeling Data Reuse in Deep Neural Networks by Taking Data-Types into Cognizance. IEEE Trans. Computers 70(9): 1526-1538 (2021) - [c24]Saksham Sharma, Vanshika V. Bhargava, Aditya Kumar Singh, Kshitij Bhardwaj, Sparsh Mittal:
Leveraging Prediction Confidence For Versatile Optimizations to CNNs. AIMLSystems 2021: 2:1-2:7 - [c23]Bhargav Achary Dandpati Kumar, R. Sai Chandra Teja
, Sparsh Mittal, Biswabandan Panda, C. Krishna Mohan:
Inferring DNN layer-types through a Hardware Performance Counters based Side Channel Attack. AIMLSystems 2021: 4:1-4:7 - 2020
- [j53]Sparsh Mittal
:
A survey on evaluating and optimizing performance of Intel Xeon Phi. Concurr. Comput. Pract. Exp. 32(19) (2020) - [j52]Nandan Kumar Jha, Sparsh Mittal, Binod Kumar, Govardhan Mattela:
DeepPeep: Exploiting Design Ramifications to Decipher the Architecture of Compact DNNs. ACM J. Emerg. Technol. Comput. Syst. 17(1): 5:1-5:25 (2020) - [j51]Sparsh Mittal:
A survey on modeling and improving reliability of DNN algorithms and accelerators. J. Syst. Archit. 104: 101689 (2020) - [j50]Sparsh Mittal
:
A survey of FPGA-based accelerators for convolutional neural networks. Neural Comput. Appl. 32(4): 1109-1139 (2020) - [c22]Poonam Rajput
, Sparsh Mittal
, Sarthak Narayan
:
Improving Accuracy and Efficiency of Object Detection Algorithms Using Multiscale Feature Aggregation Plugins. ANNPR 2020: 65-76 - [c21]Poonam Rajput, Subhrajit Nag, Sparsh Mittal:
Detecting Usage of Mobile Phones using Deep Learning Technique. GOODTECHS 2020: 96-101 - [c20]Nandan Kumar Jha, Shreyas Ravishankar, Sparsh Mittal, Arvind Kaushik, Dipan Mandal, Mahesh Chandra
:
DRACO: Co-Optimizing Hardware Utilization, and Performance of DNNs on Systolic Accelerator. ISVLSI 2020: 574-579 - [c19]Nandan Kumar Jha, Rajat Saini, Subhrajit Nag, Sparsh Mittal:
E2GC: Energy-efficient Group Convolution in Deep Neural Networks. VLSID 2020: 155-160 - [c18]Rajat Saini, Nandan Kumar Jha, Bedanta Das, Sparsh Mittal, C. Krishna Mohan
:
ULSAM: Ultra-Lightweight Subspace Attention Module for Compact Convolutional Neural Networks. WACV 2020: 1616-1625 - [i20]Nandan Kumar Jha, Sparsh Mittal, Govardhan Mattela:
The Ramifications of Making Deep Neural Networks Compact. CoRR abs/2006.15098 (2020) - [i19]Nandan Kumar Jha, Rajat Saini, Subhrajit Nag, Sparsh Mittal:
E2GC: Energy-efficient Group Convolution in Deep Neural Networks. CoRR abs/2006.15100 (2020) - [i18]Rajat Saini, Nandan Kumar Jha, Bedanta Das, Sparsh Mittal, C. Krishna Mohan:
ULSAM: Ultra-Lightweight Subspace Attention Module for Compact Convolutional Neural Networks. CoRR abs/2006.15102 (2020) - [i17]Nandan Kumar Jha, Shreyas Ravishankar, Sparsh Mittal, Arvind Kaushik, Dipan Mandal, Mahesh Chandra:
DRACO: Co-Optimizing Hardware Utilization, and Performance of DNNs on Systolic Accelerator. CoRR abs/2006.15103 (2020) - [i16]Nandan Kumar Jha, Rajat Saini, Sparsh Mittal:
On the Demystification of Knowledge Distillation: A Residual Network Perspective. CoRR abs/2006.16589 (2020) - [i15]Nandan Kumar Jha, Sparsh Mittal, Binod Kumar, Govardhan Mattela:
DeepPeep: Exploiting Design Ramifications to Decipher the Architecture of Compact DNNs. CoRR abs/2007.15248 (2020) - [i14]Nandan Kumar Jha, Sparsh Mittal:
Modeling Data Reuse in Deep Neural Networks by Taking Data-Types into Cognizance. CoRR abs/2008.02565 (2020)
2010 – 2019
- 2019
- [j49]Sparsh Mittal
:
A survey of techniques for dynamic branch prediction. Concurr. Comput. Pract. Exp. 31(1) (2019) - [j48]Sparsh Mittal
, Venkat Mattela:
A survey of techniques for improving efficiency of mobile web browsing. Concurr. Comput. Pract. Exp. 31(15) (2019) - [j47]Sumanth Umesh
, Sparsh Mittal
:
A survey of spintronic architectures for processing-in-memory and neural networks. J. Syst. Archit. 97: 349-372 (2019) - [j46]Sparsh Mittal
, Subhrajit Nag:
A survey of encoding techniques for reducing data-movement energy. J. Syst. Archit. 97: 373-396 (2019) - [j45]Sparsh Mittal
:
A Survey on optimized implementation of deep learning models on the NVIDIA Jetson platform. J. Syst. Archit. 97: 428-442 (2019) - [j44]Sparsh Mittal
:
A survey on applications and architectural-optimizations of Micron's Automata Processor. J. Syst. Archit. 98: 135-164 (2019) - [j43]Sparsh Mittal
, Shraiysh Vaishay:
A survey of techniques for optimizing deep learning on GPUs. J. Syst. Archit. 99 (2019) - [j42]Sparsh Mittal
:
A Survey of ReRAM-Based Architectures for Processing-In-Memory and Neural Networks. Mach. Learn. Knowl. Extr. 1(1): 75-114 (2019) - [c17]Haonan Wang, Mohamed Assem Ibrahim
, Sparsh Mittal, Adwait Jog:
Address-stride assisted approximate load value prediction in GPUs. ICS 2019: 184-194 - [c16]Nandan Kumar Jha, Sparsh Mittal
, Govardhan Mattela:
The Ramifications of Making Deep Neural Networks Compact. VLSID 2019: 215-220 - 2018
- [j41]Ahmed Izzat Alsalibi
, Sparsh Mittal
, Mohammed Azmi Al-Betar
, Putra Bin Sumari:
A survey of techniques for architecting SLC/MLC/TLC hybrid Flash memory-based SSDs. Concurr. Comput. Pract. Exp. 30(13) (2018) - [j40]Sparsh Mittal, Ahmed Izzat Alsalibi:
A Survey of Techniques for Improving Security of Non-volatile Memories. J. Hardw. Syst. Secur. 2(2): 179-200 (2018) - [j39]Sparsh Mittal
, S. B. Abhinaya, Manish Reddy, Irfan Ali:
A Survey of Techniques for Improving Security of GPUs. J. Hardw. Syst. Secur. 2(3): 266-285 (2018) - [j38]Sparsh Mittal
, Maruthi Seshidhar Inukonda:
A survey of techniques for improving error-resilience of DRAM. J. Syst. Archit. 91: 11-40 (2018) - [i13]Sparsh Mittal, S. B. Abhinaya, Manish Reddy, Irfan Ali:
A Survey of Techniques for Improving Security of GPUs. CoRR abs/1804.00114 (2018) - [i12]Sparsh Mittal:
A Survey of Techniques for Dynamic Branch Prediction. CoRR abs/1804.00261 (2018) - 2017
- [j37]Guoliang Zhu
, Kai Lu, Xiaoping Wang, Yiming Zhang, Pengfei Zhang, Sparsh Mittal
:
SwapX: An NVM-Based Hierarchical Swapping Framework. IEEE Access 5: 16383-16392 (2017) - [j36]Sparsh Mittal
, Jeffrey S. Vetter, Lei Jiang:
Addressing Read-Disturbance Issue in STT-RAM by Data Compression and Selective Duplication. IEEE Comput. Archit. Lett. 16(2): 94-98 (2017) - [j35]Rujia Wang, Sparsh Mittal
, Youtao Zhang, Jun Yang:
Decongest: Accelerating Super-Dense PCM Under Write Disturbance by Hot Page Remapping. IEEE Comput. Archit. Lett. 16(2): 107-110 (2017) - [j34]Sparsh Mittal
:
A Survey of Soft-Error Mitigation Techniques for Non-Volatile Memories. Comput. 6(1): 8 (2017) - [j33]Sparsh Mittal
:
A survey of techniques for designing and managing CPU register file. Concurr. Comput. Pract. Exp. 29(4) (2017) - [j32]Sparsh Mittal
:
A survey of techniques for architecting TLBs. Concurr. Comput. Pract. Exp. 29(10) (2017) - [j31]Sparsh Mittal
:
A survey of value prediction techniques for leveraging value locality. Concurr. Comput. Pract. Exp. 29(21) (2017) - [j30]Sparsh Mittal
:
A Survey of Techniques for Cache Partitioning in Multicore Processors. ACM Comput. Surv. 50(2): 27:1-27:39 (2017) - [j29]Sparsh Mittal
:
A Survey of Techniques for Architecting and Managing GPU Register File. IEEE Trans. Parallel Distributed Syst. 28(1): 16-28 (2017) - [c15]Lei Jiang, Sparsh Mittal
, Wujie Wen:
Building a Fast and Power Efficient Inductive Charge Pump System for 3D Stacked Phase Change Memories. ACM Great Lakes Symposium on VLSI 2017: 275-280 - [c14]Sparsh Mittal
, Rajendra Bishnoi, Fabian Oboril, Haonan Wang, Mehdi Baradaran Tahoori, Adwait Jog, Jeffrey S. Vetter:
Architecting SOT-RAM Based GPU Register File. ISVLSI 2017: 38-44 - [c13]Sparsh Mittal
, Haonan Wang, Adwait Jog, Jeffrey S. Vetter:
Design and Analysis of Soft-Error Resilience Mechanisms for GPU Register File. VLSID 2017: 409-414 - [i11]Sparsh Mittal:
Mitigating Read-disturbance Errors in STT-RAM Caches by Using Data Compression. CoRR abs/1711.06790 (2017) - 2016
- [j28]Sparsh Mittal
:
A Survey of Techniques for Architecting and Managing Asymmetric Multicore Processors. ACM Comput. Surv. 48(3): 45:1-45:38 (2016) - [j27]Sparsh Mittal
:
A Survey of Architectural Techniques for Managing Process Variation. ACM Comput. Surv. 48(4): 54:1-54:29 (2016) - [j26]Sparsh Mittal
:
A Survey of Techniques for Approximate Computing. ACM Comput. Surv. 48(4): 62:1-62:33 (2016) - [j25]Sparsh Mittal
:
A Survey of Recent Prefetching Techniques for Processor Caches. ACM Comput. Surv. 49(2): 35:1-35:35 (2016) - [j24]Sparsh Mittal:
A survey of power management techniques for phase change memory. Int. J. Comput. Aided Eng. Technol. 8(4): 424-444 (2016) - [j23]Sparsh Mittal
, Jeffrey S. Vetter:
Reliability Tradeoffs in Design of Volatile and Nonvolatile Caches. J. Circuits Syst. Comput. 25(11): 1650139:1-1650139:14 (2016) - [j22]Sparsh Mittal
:
A Survey of Architectural Techniques for Near-Threshold Computing. ACM J. Emerg. Technol. Comput. Syst. 12(4): 46:1-46:26 (2016) - [j21]Sparsh Mittal
:
A Survey of Techniques for Architecting Processor Components Using Domain-Wall Memory. ACM J. Emerg. Technol. Comput. Syst. 13(2): 29:1-29:25 (2016) - [j20]Sparsh Mittal
:
A Survey of Techniques for Cache Locking. ACM Trans. Design Autom. Electr. Syst. 21(3): 49:1-49:24 (2016) - [j19]Sparsh Mittal
, Jeffrey S. Vetter:
A Survey of Techniques for Modeling and Improving Reliability of Computing Systems. IEEE Trans. Parallel Distributed Syst. 27(4): 1226-1238 (2016) - [j18]Sparsh Mittal
, Jeffrey S. Vetter:
A Survey Of Architectural Approaches for Data Compression in Cache and Main Memory Systems. IEEE Trans. Parallel Distributed Syst. 27(5): 1524-1536 (2016) - [j17]Sparsh Mittal
, Jeffrey S. Vetter:
A Survey of Software Techniques for Using Non-Volatile Memories for Storage and Main Memory Systems. IEEE Trans. Parallel Distributed Syst. 27(5): 1537-1550 (2016) - [j16]Sparsh Mittal
, Jeffrey S. Vetter:
A Survey Of Techniques for Architecting DRAM Caches. IEEE Trans. Parallel Distributed Syst. 27(6): 1852-1863 (2016) - [j15]Sparsh Mittal
, Jeffrey S. Vetter:
EqualWrites: Reducing Intra-Set Write Variations for Enhancing Lifetime of Non-Volatile Caches. IEEE Trans. Very Large Scale Integr. Syst. 24(1): 103-114 (2016) - [c12]Sparsh Mittal
, Jeffrey S. Vetter:
Reducing Soft-error Vulnerability of Caches using Data Compression. ACM Great Lakes Symposium on VLSI 2016: 197-202 - [c11]Panruo Wu, Dong Li, Zizhong Chen
, Jeffrey S. Vetter, Sparsh Mittal
:
Algorithm-Directed Data Placement in Explicitly Managed Non-Volatile Memory. HPDC 2016: 141-152 - 2015
- [j14]Sparsh Mittal
, Jeffrey S. Vetter:
AYUSH: A Technique for Extending Lifetime of SRAM-NVM Hybrid Caches. IEEE Comput. Archit. Lett. 14(2): 115-118 (2015) - [j13]Jeffrey S. Vetter, Sparsh Mittal
:
Opportunities for Nonvolatile Memory Systems in Extreme-Scale High-Performance Computing. Comput. Sci. Eng. 17(2): 73-82 (2015) - [j12]Sparsh Mittal
, Jeffrey S. Vetter:
A Survey of CPU-GPU Heterogeneous Computing Techniques. ACM Comput. Surv. 47(4): 69:1-69:35 (2015) - [j11]Sparsh Mittal
, Jeffrey S. Vetter, Dong Li:
A Survey Of Architectural Approaches for Managing Embedded DRAM and Non-Volatile On-Chip Caches. IEEE Trans. Parallel Distributed Syst. 26(6): 1524-1537 (2015) - [c10]Matt Poremba, Sparsh Mittal, Dong Li, Jeffrey S. Vetter, Yuan Xie:
DESTINY: a tool for modeling emerging 3D NVM and eDRAM caches. DATE 2015: 1543-1546 - [c9]Sparsh Mittal
, Jeffrey S. Vetter:
AYUSH: Extending Lifetime of SRAM-NVM Way-Based Hybrid Caches Using Wear-Leveling. MASCOTS 2015: 112-121 - 2014
- [j10]Sparsh Mittal
, Jeffrey S. Vetter:
A Survey of Methods for Analyzing and Improving GPU Energy Efficiency. ACM Comput. Surv. 47(2): 19:1-19:23 (2014) - [j9]Sparsh Mittal
:
A survey of techniques for improving energy efficiency in embedded computing systems. Int. J. Comput. Aided Eng. Technol. 6(4): 440-459 (2014) - [j8]Sparsh Mittal
:
A study of successive over-relaxation method parallelisation over modern HPC languages. Int. J. High Perform. Comput. Netw. 7(4): 292-298 (2014) - [j7]Sparsh Mittal
:
A Survey of Techniques for Managing and Leveraging Caches in GPUs. J. Circuits Syst. Comput. 23(8) (2014) - [j6]Sparsh Mittal
, Zhao Zhang:
Encache: a Dynamic Profiling-Based Reconfiguration Technique for Improving Cache Energy Efficiency. J. Circuits Syst. Comput. 23(10) (2014) - [j5]Sparsh Mittal
:
A survey of architectural techniques for improving cache power efficiency. Sustain. Comput. Informatics Syst. 4(1): 33-43 (2014) - [j4]Sparsh Mittal
, Yanan Cao, Zhao Zhang:
MASTER: A Multicore Cache Energy-Saving Technique Using Dynamic Cache Reconfiguration. IEEE Trans. Very Large Scale Integr. Syst. 22(8): 1653-1665 (2014) - [c8]Sparsh Mittal
, Jeffrey S. Vetter, Dong Li:
WriteSmoothing: improving lifetime of non-volatile caches using intra-set wear-leveling. ACM Great Lakes Symposium on VLSI 2014: 139-144 - [c7]Sparsh Mittal
, Jeffrey S. Vetter, Dong Li:
Improving energy efficiency of embedded DRAM caches for high-end computing systems. HPDC 2014: 99-110 - [c6]Sparsh Mittal
, Jeffrey S. Vetter, Dong Li:
LastingNVCache: A Technique for Improving the Lifetime of Non-volatile Caches. ISVLSI 2014: 534-540 - [c5]Sparsh Mittal, Jeffrey S. Vetter:
EqualChance: Addressing Intra-set Write Variation to Increase Lifetime of Non-volatile Caches. INFLOW 2014 - [c4]Li Yu, Dong Li, Sparsh Mittal
, Jeffrey S. Vetter:
Quantitatively Modeling Application Resilience with the Data Vulnerability Factor. SC 2014: 695-706 - [i10]Sparsh Mittal:
A Study of Successive Over-relaxation Method Parallelization Over Modern HPC Languages. CoRR abs/1401.0763 (2014) - [i9]Sparsh Mittal:
A Survey of Techniques For Improving Energy Efficiency in Embedded Computing Systems. CoRR abs/1401.0765 (2014) - [i8]Sparsh Mittal, Jeffrey S. Vetter:
A Survey of Methods For Analyzing and Improving GPU Energy Efficiency. CoRR abs/1404.4629 (2014) - [i7]Sparsh Mittal:
Power Management Techniques for Data Centers: A Survey. CoRR abs/1404.6681 (2014) - 2013
- [j3]Sparsh Mittal
, Saket Gupta, Ankush Mittal:
BioinQA: metadata-based multi-document QA system for addressing the issues in biomedical domain. Int. J. Data Min. Model. Manag. 5(1): 37-56 (2013) - [c3]Sparsh Mittal
, Zhao Zhang, Jeffrey S. Vetter:
FlexiWay: A cache energy saving technique using fine-grained cache reconfiguration. ICCD 2013: 100-107 - [c2]Sparsh Mittal
, Zhao Zhang, Yanan Cao:
CASHIER: A Cache Energy Saving Technique for QoS Systems. VLSI Design 2013: 43-48 - [i6]Sparsh Mittal:
Energy Saving Techniques for Phase Change Memory (PCM). CoRR abs/1309.3785 (2013) - [i5]Sparsh Mittal:
A Cache-Coloring Based Technique for Saving Leakage Energy In Multitasking Systems. CoRR abs/1309.5647 (2013) - [i4]Sparsh Mittal:
A Cache Reconfiguration Approach for Saving Leakage and Refresh Energy in Embedded DRAM Caches. CoRR abs/1309.7082 (2013) - [i3]Sparsh Mittal:
Dynamic cache reconfiguration based techniques for improving cache energy efficiency. CoRR abs/1310.4231 (2013) - [i2]Sparsh Mittal:
Using Cache-coloring to Mitigate Inter-set Write Variation in Non-volatile Caches. CoRR abs/1310.8494 (2013) - [i1]Sparsh Mittal:
A Technique for Efficiently Managing SRAM-NVM Hybrid Cache. CoRR abs/1311.0170 (2013) - 2012
- [j2]Sparsh Mittal
:
A survey of architectural techniques for DRAM power management. Int. J. High Perform. Syst. Archit. 4(2): 110-119 (2012) - [c1]Sparsh Mittal
, Zhao Zhang:
Palette: A Cache Leakage Energy Saving Technique for Green Computing. High Performance Computing Workshop (2) 2012: 46-61 - 2011
- [j1]Sparsh Mittal
, Ankush Mittal:
Versatile question answering systems: seeing in synthesis. Int. J. Intell. Inf. Database Syst. 5(2): 119-142 (2011)
Coauthor Index
![](https://dblp.org/img/cog.dark.24x24.png)
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.
Reference lists
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.
Citation data
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.
OpenAlex data
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 2024-08-07 21:34 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint