| Scheduling Techniques for GPU Architectures with Processing-in-Memory Capabilities A Pattnaik, X Tang, A Jog, O Kayiran, AK Mishra, MT Kandemir, O Mutlu, ... Proceedings of the 25th International Conference on Parallel Architecture …, 2016 | 242 | 2016 |
| Anatomy of GPU Memory System for Multi-application Execution A Jog, O Kayiran, T Kesten, A Pattnaik, E Bolotin, N Chatterjee, ... Proceedings of the 2015 International Symposium on Memory Systems, 223-234, 2015 | 117 | 2015 |
| Exploiting Core Criticality for Enhanced GPU Performance A Jog, O Kayiran, A Pattnaik, MT Kandemir, O Mutlu, R Iyer, CR Das Proceedings of the 2016 ACM SIGMETRICS International Conference on …, 2016 | 76* | 2016 |
| Controlled Kernel Launch for Dynamic Parallelism in GPUs X Tang, A Pattnaik, H Jiang, O Kayiran, A Jog, MI Sreepathi Pai, ... Proceedings of the 23rd IEEE Symposium on High Performance Computer …, 2017 | 62 | 2017 |
| A New and Efficient Method for Removal of High Density Salt and Pepper Noise through Cascade Decision Based Filtering Algorithm A Pattnaik, S Agarwal, S Chand Procedia Technology 6, 108-117, 2012 | 57 | 2012 |
| Opportunistic Computing in GPU Architectures A Pattnaik, X Tang, O Kayiran, A Jog, A Mishra, MT Kandemir, ... Proceedings of the 46th Annual International Symposium on Computer Architecture, 2019 | 56 | 2019 |
| NEBULA: A Neuromorphic Spin-Based Ultra-Low Power Architecture for SNNs and ANNs S Singh, A Sarma, N Jao, A Pattnaik, S Lu, K Yang, A Sengupta, ... | 52 | 2020 |
| μC-States: Fine-grained GPU Datapath Power Management O Kayiran, A Jog, A Pattnaik, R Ausavarungnirun, X Tang, MT Kandemir, ... Parallel Architecture and Compilation Techniques (PACT), 2016 International …, 2016 | 51 | 2016 |
| Measuring and Modeling On-chip Interconnect Power on Real Hardware V Adhinarayanan, I Paul, JL Greathouse, W Huang, A Pattnaik, W Feng Workload Characterization (IISWC), 2016 IEEE International Symposium on, 1-11, 2016 | 33 | 2016 |
| Distilling the essence of raw video to reduce memory usage and energy at edge devices H Zhang, S Zhao, A Pattnaik, MT Kandemir, A Sivasubramaniam, CR Das Proceedings of the 52nd Annual IEEE/ACM international symposium on …, 2019 | 16 | 2019 |
| Quantifying data locality in dynamic parallelism in GPUs X Tang, A Pattnaik, O Kayiran, A Jog, MT Kandemir, C Das Proceedings of the ACM on Measurement and Analysis of Computing Systems 2 (3 …, 2018 | 9 | 2018 |
| Robotic Arm Control through Human Arm Movement using Accelerometers A Pattnaik, R Ranjan | 9 | 2013 |
| Quantifying data locality in dynamic parallelism in gpus X Tang, A Pattnaik, O Kayiran, A Jog, MT Kandemir, C Das ACM SIGMETRICS Performance Evaluation Review 47 (1), 25-26, 2019 | 8 | 2019 |
| CASH: compiler assisted hardware design for improving DRAM energy efficiency in CNN inference A Sarma, H Jiang, A Pattnaik, J Kotra, MT Kandemir, CR Das Proceedings of the International Symposium on Memory Systems, 396-407, 2019 | 7 | 2019 |
| Exploiting activation based gradient output sparsity to accelerate backpropagation in cnns A Sarma, S Singh, H Jiang, A Pattnaik, AK Mishra, V Narayanan, ... arXiv preprint arXiv:2109.07710, 2021 | 4 | 2021 |
| ScaleDNN: data movement aware DNN training on multi-GPU W Xu, A Pattnaik, G Yuan, Y Wang, Y Zhang, X Tang 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 1-9, 2021 | 1 | 2021 |
| Be(-A)ware of Data Movement: Optimizing Throughput Processors For Efficient Computations A Pattnaik The Pennsylvania State University, 2019 | | 2019 |
Chita R. DasPenn State UniversityVerified email at cse.psu.edu