Scenario Based Mapping of Dynamic Applications on MPSoC: A 3D Graphics Case Study. - Narasinga Rao Miniskar; Elena Hammari; Satyakiran Munaga; Stylianos Mamagkakis; Per Gunnar Kjeldsberg; Francky Catthoor (SAMOS, 2009)

PinComm: Characterizing Intra-application Communication for the Many-Core Era. - Wim Heirman; Dirk Stroobandt; Narasinga Rao Miniskar; Roel Wuyts; Francky Catthoor (ICPADS, 2010)

SAMOSA: Scratchpad aware mapping of streaming applications. - Zubair Wadood Bhatti; Davy Preuveneers; Yolande Berbers; Narasinga Rao Miniskar; Roel Wuyts (SoC, 2011)

Function inlining and loop unrolling for loop acceleration in reconfigurable processors. - Narasinga Rao Miniskar; Pankaj Shailendra Gode; Soma Kohli; Donghoon Yoo (CASES, 2012)

Memory and communication driven spatio-temporal scheduling on MPSoCs. - Zubair Wadood Bhatti; Narasinga Rao Miniskar; Davy Preuveneers; Roel Wuyts; Yolande Berbers; Francky Catthoor (SBCCI, 2012)

System Scenario Based Resource Management of Processing Elements on MPSoC (Systeemscenario-gebaseerd beheer van taken op multiprocessor systemen-op-chip (MPSoC)). - Narasinga Rao Miniskar (2012)

Retargetable automatic generation of compound instructions for CGRA based reconfigurable processor applications. - Narasinga Rao Miniskar; Soma Kohli; Haewoo Park; Donghoon Yoo (CASES, 2014)

Intra mode power saving methodology for CGRA-based reconfigurable processor architectures. - Narasinga Rao Miniskar; Rahul R. Patil; Raj Narayana Gadde; Young-chul Rams Cho; Sukjin Kim; Shi Hwa Lee (ISCAS, 2016)

A novel method to regenerate an optimal CNN by exploiting redundancy patterns in the network. - Sirish Kumar Pasupuleti; Narasinga Rao Miniskar; Vasanthakumar Rajagopal; Raj Narayana Gadde (ICIP, 2017)

Fast cycle-accurate compile based simulator for reconfigurable processor. - Narasinga Rao Miniskar; Raj Narayana Gadde; Young-chul Rams Cho; Sukjin Kim (ISCAS, 2017)

An Intelligent Bandwidth Manager for CNN Applications on Embedded Devices. - Sirish Kumar Pasupuleti; Aishwarya Rajaram; Narasinga Rao Miniskar; Raj Narayana Gadde; Deepanshu Yadvandu; Vasanthakumar Rajagopal; Ashok Vishnoi; Chandra Kumar Ramasamy (ICIP, 2018)

Accurate and Efficient Fixed Point Inference for Deep Neural Networks. - Vasanthakumar Rajagopal; Chandra Kumar Ramasamy; Ashok Vishnoi; Raj Narayana Gadde; Narasinga Rao Miniskar; Sirish Kumar Pasupuleti (ICIP, 2018)

Optimal SDRAM Buffer Allocator for Efficient Reuse of Layer IO in CNNs Inference Framework. - Narasinga Rao Miniskar; Sirish Kumar Pasupuleti; Vasanthakumar Rajagopal; Ashok Vishnoi; Chandra Kumar Ramasamy; Raj Narayana Gadde (ISCAS, 2018)

Low Complex & High Accuracy Computation Approximations to Enable On-Device RNN Applications. - Sirish Kumar Pasupuleti; Raj Narayana Gadde; Vasanthakumar Rajagopal; Ashok Vishnoi; N. Chandra Sekhar; R. Chandra Kumar; Narasinga Rao Miniskar (ISCAS, 2019)

Deffe: a data-efficient framework for performance characterization in domain-specific computing. - Frank Liu 001; Narasinga Rao Miniskar; Dwaipayan Chakraborty; Jeffrey S. Vetter (CF, 2020)

Deffe. - Frank Liu 001; Narasinga Rao Miniskar; Dwaipayan Chakraborty; Jeffrey S. Vetter (Zenodo, 2020)

Deffe. - Frank Liu 001; Narasinga Rao Miniskar; Dwaipayan Chakraborty; Jeffrey S. Vetter (Zenodo, 2020)

Toward Performance Portable Programming for Heterogeneous Systems on a Chip: A Case Study with Qualcomm Snapdragon SoC. - Anthony M. Cabrera; Seth Hitefield; Jungwon Kim; Seyong Lee; Narasinga Rao Miniskar; Jeffrey S. Vetter (HPEC, 2021)

A Memory Efficient Lock-Free Circular Queue. - Narasinga Rao Miniskar; Frank Liu 001; Jeffrey S. Vetter (ISCAS, 2021)

A Hierarchical Task Scheduler for Heterogeneous Computing. - Narasinga Rao Miniskar; Frank Liu 001; Aaron R. Young; Dwaipayan Chakraborty; Jeffrey S. Vetter (ISC, 2021)

Ultra Low Latency Machine Learning for Scientific Edge Applications. - Narasinga Rao Miniskar; Aaron R. Young; Frank Liu 001; Willem Blokland; Anthony M. Cabrera; Jeffrey S. Vetter (FPL, 2022)

IRIS-BLAS: Towards a Performance Portable and Heterogeneous BLAS Library. - Narasinga Rao Miniskar; Mohammad Alaul Haque Monil; Pedro Valero-Lara; Frank Liu 001; Jeffrey S. Vetter (HIPC, 2022)

LaRIS: Targeting Portability and Productivity for LAPACK Codes on Extreme Heterogeneous Systems by Using IRIS. - Mohammad Alaul Haque Monil; Narasinga Rao Miniskar; Frank Y. Liu; Jeffrey S. Vetter; Pedro Valero-Lara (RSDHA@SC, 2022)

Adrastea: An Efficient FPGA Design Environment for Heterogeneous Scientific Computing and Machine Learning. - Aaron R. Young; Narasinga Rao Miniskar; Frank Liu 001; Willem Blokland; Jeffrey S. Vetter (SMC, 2022)

IRIS-DMEM: Efficient Memory Management for Heterogeneous Computing. - Narasinga Rao Miniskar; Mohammad Alaul Haque Monil; Pedro Valero-Lara; Frank Y. Liu; Jeffrey S. Vetter (HPEC, 2023)

On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments. - Shruti R. Kulkarni; Aaron R. Young; Prasanna Date; Narasinga Rao Miniskar; Jeffrey S. Vetter; Farah Fahim; Benjamin Parpillon; Jennet Dickinson; Nhan Tran; Jieun Yoo; Corrinne Mills; Morris Swartz; et al. (ICONS, 2023)

An FPGA-Based Neuromorphic Processor with All-to-All Connectivity. - Disha Maheshwari; Aaron R. Young; Prasanna Date; Shruti R. Kulkarni; Brett Witherspoon; Narasinga Rao Miniskar (ICRC, 2023)

A 3D Implementation of Convolutional Neural Network for Fast Inference. - Narasinga Rao Miniskar; Pruek Vanna-Iampikul; Aaron R. Young; Sung Kyu Lim; Frank Liu 001; Jieun Yoo; Corrinne Mills; Nhan Tran; Farah Fahim; Jeffrey S. Vetter (ISCAS, 2023)

Tiling Framework for Heterogeneous Computing of Matrix based Tiled Algorithms. - Narasinga Rao Miniskar; Mohammad Alaul Haque Monil; Pedro Valero-Lara; Frank Liu 001; Jeffrey S. Vetter (ExHET@PPoPP, 2023)

MatRIS: Multi-level Math Library Abstraction for Heterogeneity and Performance Portability using IRIS Runtime. - Mohammad Alaul Haque Monil; Narasinga Rao Miniskar; Keita Teranishi; Jeffrey S. Vetter; Pedro Valero-Lara (SC Workshops, 2023)

Abisko: Deep codesign of an architecture for spiking neural networks using novel neuromorphic materials. - Jeffrey S. Vetter; Prasanna Date; Farah Fahim; Shruti R. Kulkarni; Petro Maksymovych; A. Alec Talin; Marc González Tallada; Pruek Vanna-Iampikul; Aaron R. Young; David Brooks 001; Yu Cao 001; Gu-Yeon Wei; et al. (Int. J. High Perform. Comput. Appl., 2023)

CHARM-SYCL & IRIS: A Tool Chain for Performance Portability on Extremely Heterogeneous Systems. - Norihisa Fujita; Beau Johnston; Narasinga Rao Miniskar; Ryohei Kobayashi 001; Mohammad Alaul Haque Monil; Keita Teranishi; Seyong Lee; Jeffrey S. Vetter; Taisuke Boku (e-Science, 2024)

IRIS-MEMFLOW: Data Flow-Enabled Portable Memory Orchestration in IRIS Runtime for Diverse Heterogeneity. - Mohammad Alaul Haque Monil; Narasinga Rao Miniskar; Seyong Lee; Beau Johnston; Pedro Valero-Lara; Aaron R. Young; Keita Teranishi; Jeffrey S. Vetter (HPEC, 2024)

Neuro-Spark: A Submicrosecond Spiking Neural Networks Architecture for In-Sensor Filtering. - Narasinga Rao Miniskar; Aaron R. Young; Kazi Asifuzzaman; Shruti R. Kulkarni; Prasanna Date; Alice Bean; Jeffrey S. Vetter (ICONS, 2024)

IRIS: Exploring Performance Scaling of the Intelligent Runtime System and its Dynamic Scheduling Policies. - Beau Johnston; Narasinga Rao Miniskar; Aaron R. Young; Mohammad Alaul Haque Monil; Seyong Lee; Jeffrey S. Vetter (IPDPS (Workshops), 2024)

COSMIC DAWN: Distributed Analysis of Wireless at Nextscale. - Michael M. Wise; Narasinga Rao Miniskar; Seth D. Hitefield; Mohammed M. Olama; Jeffrey S. Vetter (MILCOM, 2024)

IRIS-GNN: Leveraging Graph Neural Networks for Scheduling on Truly Heterogeneous Runtime Systems. - Beau Johnston; Thibault de Boissiere; Mohammad Alaul Haque Monil; Narasinga Rao Miniskar; Aaron R. Young; Seyong Lee; Jeffrey S. Vetter (SC Workshops, 2024)

IRIS Reimagined: Advancements in Intelligent Runtime System for Task-Based Programming. - Narasinga Rao Miniskar; Seyong Lee; Beau Johnston; Aaron R. Young; Mohammad Alaul Haque Monil; Pedro Valero-Lara; Jeffrey S. Vetter (WAMTA, 2024)

MatRIS: Addressing the Challenges for Portability and Heterogeneity Using Tasking for Matrix Decomposition (Cholesky). - Mohammad Alaul Haque Monil; Narasinga Rao Miniskar; Pedro Valero-Lara; Keita Teranishi; Jeffrey S. Vetter (WAMTA, 2024)

Mapping Spiking Neural Networks to Heterogeneous Crossbar Architectures using Integer Linear Programming. - Devin Pohl; Aaron R. Young; Kazi Asifuzzaman; Narasinga Rao Miniskar; Jeffrey S. Vetter (DATE, 2025)

ReSpike: A Co-Design Framework for Evaluating SNNs on ReRAM-Based Neuromorphic Processors. - Kazi Asifuzzaman; Aaron R. Young; Prasanna Date; Shruti R. Kulkarni; Narasinga Rao Miniskar; Matthew J. Marinella; Jeffrey S. Vetter (Euro-Par (2), 2025)

Performance Impact and Trade-Offs for Tuning Key Architectural Parameters on CPU+GPU Systems. - Kazi Asifuzzaman; Narasinga Rao Miniskar; William F. Godoy; Oscar R. Hernandez; Jeffrey S. Vetter (GPGPU@PPoPP, 2025)

IRISX: A Dynamic Trade-off System for Harnessing Heterogeneity for Performance Portability. - Sanil Rao; Mohammad Alaul Haque Monil; Het Mankad; Narasinga Rao Miniskar; Keita Teranishi; Jeffrey S. Vetter; Franz Franchetti (IPDPS (Workshops), 2025)

Characterizing GPU Energy Usage in Exascale-Ready Portable Science Applications. - William F. Godoy; Oscar R. Hernandez; Paul R. C. Kent; Maria Patrou; Kazi Asifuzzaman; Narasinga Rao Miniskar; Pedro Valero-Lara; Jeffrey S. Vetter; Matthew D. Sinclair; Jason Lowe-Power; Bobby R. Bruce (CoRR, 2025)

Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions. - Keita Teranishi; Harshitha Menon; William F. Godoy; Prasanna Balaprakash; David Bau; Tal Ben-Nun; Abhinav Bhatele; Franz Franchetti; Michael E. Franusich; Todd Gamblin; Giorgis Georgakoudis; Tom Goldstein; et al. (CoRR, 2025)