Angshuman Parashar

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 27

Top Topics

Tensor Decomposition

Structured Sparsity

Parallel Implementation

Genetic Algorithm

Top Venues

Publications

Qijing Huang, Po-An Tsai, Joel S. Emer, Angshuman Parashar
Mind the Gap: Attainable Data Movement and Operational Intensity Bounds for Tensor Algorithms. ISCA (2024)
Yannan Nellie Wu, Po-An Tsai, Saurav Muralidharan, Angshuman Parashar, Vivienne Sze, Joel Emer
HighLight: Efficient and Flexible DNN Acceleration with Hierarchical Structured Sparsity. MICRO (2023)
Yannan Nellie Wu, Po-An Tsai, Saurav Muralidharan, Angshuman Parashar, Vivienne Sze, Joel S. Emer
HighLight: Efficient and Flexible DNN Acceleration with Hierarchical Structured Sparsity. CoRR (2023)
Michael Gilbert, Yannan Nellie Wu, Angshuman Parashar, Vivienne Sze, Joel S. Emer
LoopTree: Enabling Exploration of Fused-layer Dataflow Accelerators. ISPASS (2023)
Prasanth Chatarasi, Hyoukjun Kwon, Angshuman Parashar, Michael Pellauer, Tushar Krishna, Vivek Sarkar
Marvel: A Data-Centric Approach for Mapping Deep Learning Operators on Spatial Accelerators. ACM Trans. Archit. Code Optim. 19 (1) (2022)
Yannan Nellie Wu, Po-An Tsai, Angshuman Parashar, Vivienne Sze, Joel S. Emer
Sparseloop: An Analytical Approach To Sparse Tensor Accelerator Modeling. CoRR (2022)
Sheng-Chun Kao, Michael Pellauer, Angshuman Parashar, Tushar Krishna
DiGamma: Domain-aware Genetic Algorithm for HW-Mapping Co-optimization for DNN Accelerators. DATE (2022)
Sheng-Chun Kao, Hyoukjun Kwon, Michael Pellauer, Angshuman Parashar, Tushar Krishna
A Formalism of DNN Accelerator Flexibility. SIGMETRICS (Abstracts) (2022)
Sheng-Chun Kao, Michael Pellauer, Angshuman Parashar, Tushar Krishna
DiGamma: Domain-aware Genetic Algorithm for HW-Mapping Co-optimization for DNN Accelerators. CoRR (2022)
Sheng-Chun Kao, Hyoukjun Kwon, Michael Pellauer, Angshuman Parashar, Tushar Krishna
A Formalism of DNN Accelerator Flexibility. Proc. ACM Meas. Anal. Comput. Syst. 6 (2) (2022)
Eric Qin, Raveesh Garg, Abhimanyu Bambhaniya, Michael Pellauer, Angshuman Parashar, Sivasankaran Rajamanickam, Cong Hao, Tushar Krishna
Enabling Flexibility for Sparse Tensor Acceleration via Heterogeneity. CoRR (2022)
Mark Horeni, Pooria Taheri, Po-An Tsai, Angshuman Parashar, Joel S. Emer, Siddharth Joshi
Ruby: Improving Hardware Efficiency for Tensor Algebra Accelerators Through Imperfect Factorization. ISPASS (2022)
Yannan Nellie Wu, Po-An Tsai, Angshuman Parashar, Vivienne Sze, Joel S. Emer
Sparseloop: An Analytical Approach To Sparse Tensor Accelerator Modeling. MICRO (2022)
Sheng-Chun Kao, Hyoukjun Kwon, Michael Pellauer, Angshuman Parashar, Tushar Krishna
A Formalism of DNN Accelerator Flexibility. CoRR (2022)
Sheng-Chun Kao, Angshuman Parashar, Po-An Tsai, Tushar Krishna
Demystifying Map Space Exploration for NPUs. CoRR (2022)
Sheng-Chun Kao, Angshuman Parashar, Po-An Tsai, Tushar Krishna
Demystifying Map Space Exploration for NPUs. IISWC (2022)
Geonhwa Jeong, Gokcen Kestor, Prasanth Chatarasi, Angshuman Parashar, Po-An Tsai, Sivasankaran Rajamanickam, Roberto Gioiosa, Tushar Krishna
Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators. CoRR (2021)
Kartik Hegde, Po-An Tsai, Sitao Huang, Vikas Chandra, Angshuman Parashar, Christopher W. Fletcher
Mind Mappings: Enabling Efficient Algorithm-Accelerator Mapping Space Search. CoRR (2021)
Geonhwa Jeong, Gokcen Kestor, Prasanth Chatarasi, Angshuman Parashar, Po-An Tsai, Sivasankaran Rajamanickam, Roberto Gioiosa, Tushar Krishna
Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators. PACT (2021)
Kartik Hegde, Po-An Tsai, Sitao Huang, Vikas Chandra, Angshuman Parashar, Christopher W. Fletcher
Mind mappings: enabling efficient algorithm-accelerator mapping space search. ASPLOS (2021)
Hyoukjun Kwon, Michael Pellauer, Angshuman Parashar, Tushar Krishna
Flexion: A Quantitative Metric for Flexibility in DNN Accelerators. IEEE Comput. Archit. Lett. 20 (1) (2021)
Yannan Nellie Wu, Po-An Tsai, Angshuman Parashar, Vivienne Sze, Joel S. Emer
Sparseloop: An Analytical, Energy-Focused Design Space Exploration Methodology for Sparse Tensor Accelerators. ISPASS (2021)
Hyoukjun Kwon, Prasanth Chatarasi, Vivek Sarkar, Tushar Krishna, Michael Pellauer, Angshuman Parashar
MAESTRO: A Data-Centric Approach to Understand Reuse, Performance, and Hardware Cost of DNN Mappings. IEEE Micro 40 (3) (2020)
Hyoukjun Kwon, Prasanth Chatarasi, Michael Pellauer, Angshuman Parashar, Vivek Sarkar, Tushar Krishna
Understanding Reuse, Performance, and Hardware Cost of DNN Dataflow: A Data-Centric Approach. MICRO (2019)
Angshuman Parashar, Priyanka Raina, Yakun Sophia Shao, Yu-Hsin Chen, Victor A. Ying, Anurag Mukkara, Rangharajan Venkatesan, Brucek Khailany, Stephen W. Keckler, Joel S. Emer
Timeloop: A Systematic Approach to DNN Accelerator Evaluation. ISPASS (2019)
Angshuman Parashar, Minsoo Rhu, Anurag Mukkara, Antonio Puglielli, Rangharajan Venkatesan, Brucek Khailany, Joel S. Emer, Stephen W. Keckler, William J. Dally
SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks. ISCA (2017)
Angshuman Parashar, Minsoo Rhu, Anurag Mukkara, Antonio Puglielli, Rangharajan Venkatesan, Brucek Khailany, Joel S. Emer, Stephen W. Keckler, William J. Dally
SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks. CoRR (2017)
Michael Pellauer, Angshuman Parashar, Michael Adler, Bushra Ahsan, Randy L. Allmon, Neal Clayton Crago, Kermin Fleming, Mohit Gambhir, Aamer Jaleel, Tushar Krishna, Daniel Lustig, Stephen Maresh, Vladimir Pavlov, Rachid Rayess, Antonia Zhai, Joel S. Emer
Efficient Control and Communication Paradigms for Coarse-Grained Spatial Architectures. ACM Trans. Comput. Syst. 33 (3) (2015)
Angshuman Parashar, Michael Pellauer, Michael Adler, Bushra Ahsan, Neal Clayton Crago, Daniel Lustig, Vladimir Pavlov, Antonia Zhai, Mohit Gambhir, Aamer Jaleel, Randy L. Allmon, Rachid Rayess, Stephen Maresh, Joel S. Emer
Efficient Spatial Processing Element Control via Triggered Instructions. IEEE Micro 34 (3) (2014)
Angshuman Parashar, Michael Pellauer, Michael Adler, Bushra Ahsan, Neal Clayton Crago, Daniel Lustig, Vladimir Pavlov, Antonia Zhai, Mohit Gambhir, Aamer Jaleel, Randy L. Allmon, Rachid Rayess, Stephen Maresh, Joel S. Emer
Triggered instructions: a control paradigm for spatially-programmed architectures. ISCA (2013)
Peng Li, Angshuman Parashar, Michael Pellauer, Tao Wang, Joel S. Emer
A Hierarchical Architectural Framework for Reconfigurable Logic Computing. IPDPS Workshops (2013)
Kermin Elliott Fleming, Michael Adler, Michael Pellauer, Angshuman Parashar, Arvind, Joel S. Emer
Leveraging latency-insensitivity to ease multiple FPGA design. FPGA (2012)
Michael Adler, Kermin Fleming, Angshuman Parashar, Michael Pellauer, Joel S. Emer
Leap scratchpads: automatic memory and cache management for reconfigurable logic. FPGA (2011)
Michael Pellauer, Michael Adler, Michel A. Kinsy, Angshuman Parashar, Joel S. Emer
HAsim: FPGA-based high-detail multicore simulation using time-division multiplexing. HPCA (2011)
Niranjan Soundararajan, Angshuman Parashar, Anand Sivasubramaniam
Mechanisms for bounding vulnerabilities of processor structures. ISCA (2007)
Angshuman Parashar, Anand Sivasubramaniam, Sudhanva Gurumurthi
SlicK: slice-based locality exploitation for efficient redundant multithreading. ASPLOS (2006)
Puneet Sharma, Angshuman Parashar, Subhashis Banerjee, Prem Kumar Kalra
An uncalibrated lightfield acquisition system. Image Vis. Comput. 22 (14) (2004)
Angshuman Parashar, Sudhanva Gurumurthi, Anand Sivasubramaniam
A Complexity-Effective Approach to ALU Bandwidth Enhancement for Instruction-Level Temporal Redundancy. ISCA (2004)
Puneet Sharma, Angshuman Parashar, Subhashis Banerjee, Prem Kumar Kalra
An Uncalibrated Lightfield Acquisition System. ICVGIP (2002)