GraphPIM: Enabling Instruction-Level PIM Offloading in Graph Computing Frameworks. - Lifeng Nai; Ramyad Hadidi; Jaewoong Sim; Hyojong Kim; Pranith Kumar; Hyesoon Kim (HPCA, 2017)

Demystifying the characteristics of 3D-stacked memories: A case study for Hybrid Memory Cube. - Ramyad Hadidi; Bahar Asgari; Burhan Ahmad Mudassar; Saibal Mukhopadhyay; Sudhakar Yalamanchili; Hyesoon Kim (IISWC, 2017)

CODA: Enabling Co-location of Computation and Data for Near-Data Processing. - Hyojong Kim; Ramyad Hadidi; Lifeng Nai; Hyesoon Kim; Nuwan Jayasena; Yasuko Eckert; Onur Kayiran; Gabriel H. Loh (CoRR, 2017)

CAIRO: A Compiler-Assisted Technique for Enabling Instruction-Level Offloading of Processing-In-Memory. - Ramyad Hadidi; Lifeng Nai; Hyojong Kim; Hyesoon Kim (ACM Trans. Archit. Code Optim., 2017)

Real-Time Image Recognition Using Collaborative IoT Devices. - Ramyad Hadidi; Jiashen Cao; Matthew Woodward; Michael S. Ryoo; Hyesoon Kim (ReQuEST@ASPLOS, 2018)

CoolPIM: Thermal-Aware Source Throttling for Efficient PIM Instruction Offloading. - Lifeng Nai; Ramyad Hadidi; He Xiao; Hyojong Kim; Jaewoong Sim; Hyesoon Kim (IPDPS, 2018)

Performance Implications of NoCs on 3D-Stacked Memories: Insights from the Hybrid Memory Cube. - Ramyad Hadidi; Bahar Asgari; Jeffrey S. Young 001; Burhan Ahmad Mudassar; Kartikay Garg; Tushar Krishna; Hyesoon Kim (ISPASS, 2018)

Musical Chair: Efficient Real-Time Recognition Using Collaborative IoT Devices. - Ramyad Hadidi; Jiashen Cao; Matthew Woodward; Michael S. Ryoo; Hyesoon Kim (CoRR, 2018)

Distributed Perception by Collaborative Robots. - Ramyad Hadidi; Jiashen Cao; Matthew Woodward; Michael S. Ryoo; Hyesoon Kim (IEEE Robotics Autom. Lett., 2018)

CODA: Enabling Co-location of Computation and Data for Multiple GPU Systems. - Hyojong Kim; Ramyad Hadidi; Lifeng Nai; Hyesoon Kim; Nuwan Jayasena; Yasuko Eckert; Onur Kayiran; Gabriel H. Loh (ACM Trans. Archit. Code Optim., 2018)

Video analytics from edge to server: work-in-progress. - Jiashen Cao; Ramyad Hadidi; Joy Arulraj; Hyesoon Kim (CODES+ISSS, 2019)

LODESTAR: Creating Locally-Dense CNNs for Efficient Inference on Systolic Arrays. - Bahar Asgari; Ramyad Hadidi; Hyesoon Kim; Sudhakar Yalamanchili (DAC, 2019)

Robustly Executing DNNs in IoT Systems Using Coded Distributed Computing. - Ramyad Hadidi; Jiashen Cao; Michael S. Ryoo; Hyesoon Kim (DAC, 2019)

Capella: Customizing Perception for Edge Devices by Efficiently Allocating FPGAs to DNNs. - Younmin Bae; Ramyad Hadidi; Bahar Asgari; Jiashen Cao; Hyesoon Kim (FPL, 2019)

Characterizing the Deployment of Deep Neural Networks on Commercial Edge Devices. - Ramyad Hadidi; Jiashen Cao; Yilun Xie; Bahar Asgari; Tushar Krishna; Hyesoon Kim (IISWC, 2019)

Characterizing the Execution of Deep Neural Networks on Collaborative Robots and Edge Devices. - Matthew L. Merck; Bingyao Wang; Lixing Liu; Chunjun Jia; Arthur Siqueira; Qiusen Huang; Abhijeet Saraha; Dongsuk Lim; Jiashen Cao; Ramyad Hadidi; Hyesoon Kim (PEARC, 2019)

Collaborative Execution of Deep Neural Networks on Internet of Things Devices. - Ramyad Hadidi; Jiashen Cao; Michael S. Ryoo; Hyesoon Kim (CoRR, 2019)

Thermal-aware processing-in-memory instruction offloading. - Lifeng Nai; Ramyad Hadidi; He Xiao; Hyojong Kim; Jaewoong Sim; Hyesoon Kim (J. Parallel Distributed Comput., 2019)

ERIDANUS: Efficiently Running Inference of DNNs Using Systolic Arrays. - Bahar Asgari; Ramyad Hadidi; Hyesoon Kim; Sudhakar Yalamanchili (IEEE Micro, 2019)

Batch-Aware Unified Memory Management in GPUs for Irregular Workloads. - Hyojong Kim; Jaewoong Sim; Prasun Gera; Ramyad Hadidi; Hyesoon Kim (ASPLOS, 2020)

PISCES: Power-Aware Implementation of SLAM by Customizing Efficient Sparse Algebra. - Bahar Asgari; Ramyad Hadidi; Nima Shoghi Ghaleshahi; Hyesoon Kim (DAC, 2020)

ASCELLA: Accelerating Sparse Computation by Enabling Stream Accesses to Memory. - Bahar Asgari; Ramyad Hadidi; Hyesoon Kim (DATE, 2020)

Proposing a Fast and Scalable Systolic Array for Matrix Multiplication. - Bahar Asgari; Ramyad Hadidi; Hyesoon Kim (FCCM, 2020)

ALRESCHA: A Lightweight Reconfigurable Sparse-Computation Accelerator. - Bahar Asgari; Ramyad Hadidi; Tushar Krishna; Hyesoon Kim; Sudhakar Yalamanchili (HPCA, 2020)

MEISSA: Multiplying Matrices Efficiently in a Scalable Systolic Architecture. - Bahar Asgari; Ramyad Hadidi; Hyesoon Kim (ICCD, 2020)

Understanding the Software and Hardware Stacks of a General-Purpose Cognitive Drone. - Sam Jijina; Adriana Amyette; Nima Shoghi Ghaleshahi; Ramyad Hadidi; Hyesoon Kim (ISPASS, 2020)

Edge-Tailored Perception: Fast Inferencing in-the-Edge with Efficient Model Distribution. - Ramyad Hadidi; Bahar Asgari; Jiashen Cao; Younmin Bae; Hyojong Kim; Michael S. Ryoo; Hyesoon Kim (CoRR, 2020)

Reducing Inference Latency with Concurrent Architectures for Image Recognition. - Ramyad Hadidi; Jiashen Cao; Michael S. Ryoo; Hyesoon Kim (CoRR, 2020)

Secure Location-Aware Authentication and Communication for Intelligent Transportation Systems. - Nima Shoghi Ghaleshahi; Ramyad Hadidi; Jaewon Lee; Jun Chen; Arthur Siqueira; Rahul Rajan; Shaan Dhawan; Pooya Shoghi Ghalehshahi; Hyesoon Kim (CoRR, 2020)

Copernicus: Characterizing the Performance Implications of Compression Formats Used in Sparse Workloads. - Bahar Asgari; Ramyad Hadidi; Joshua Dierberger; Charlotte Steinichen; Hyesoon Kim (CoRR, 2020)

Toward Collaborative Inferencing of Deep Neural Networks on Internet-of-Things Devices. - Ramyad Hadidi; Jiashen Cao; Michael S. Ryoo; Hyesoon Kim (IEEE Internet Things J., 2020)

Quantifying the design-space tradeoffs in autonomous drones. - Ramyad Hadidi; Bahar Asgari; Sam Jijina; Adriana Amyette; Nima Shoghi; Hyesoon Kim (ASPLOS, 2021)

FAFNIR: Accelerating Sparse Gathering by Using Efficient Near-Memory Intelligent Reduction. - Bahar Asgari; Ramyad Hadidi; Jiashen Cao; Da Eun Shim; Sung Kyu Lim; Hyesoon Kim (HPCA, 2021)

Copernicus: Characterizing the Performance Implications of Compression Formats Used in Sparse Workloads. - Bahar Asgari; Ramyad Hadidi; Joshua Dierberger; Charlotte Steinichen; Amaan Marfatia; Hyesoon Kim (IISWC, 2021)

THIA: Accelerating Video Analytics using Early Inference and Fine-Grained Query Planning. - Jiashen Cao; Ramyad Hadidi; Joy Arulraj; Hyesoon Kim (CoRR, 2021)

Creating Robust Deep Neural Networks With Coded Distributed Computing for IoT Systems. - Ramyad Hadidi; Jiashen Cao; Hyesoon Kim (CoRR, 2021)

Efficiently Solving Partial Differential Equations in a Partially Reconfigurable Specialized Hardware. - Bahar Asgari; Ramyad Hadidi; Tushar Krishna; Hyesoon Kim; Sudhakar Yalamanchili (IEEE Trans. Computers, 2021)

Deploying Deep Neural Networks in Edge with Distribution. - Ramyad Hadidi (2021)

FiGO: Fine-Grained Query Optimization in Video Analytics. - Jiashen Cao; Karan Sarkar; Ramyad Hadidi; Joy Arulraj; Hyesoon Kim (SIGMOD Conference, 2022)

Creating Robust Deep Neural Networks with Coded Distributed Computing for IoT. - Ramyad Hadidi; Jiashen Cao; Bahar Asgari; Hyesoon Kim (EDGE, 2023)

Reducing Inference Latency with Concurrent Architectures for Image Recognition at Edge. - Ramyad Hadidi; Jiashen Cao; Michael S. Ryoo; Hyesoon Kim (EDGE, 2023)

Context-Aware Task Handling in Resource-Constrained Robots with Virtualization. - Ramyad Hadidi; Nima Shoghi Ghaleshahi; Bahar Asgari; Hyesoon Kim (EDGE, 2023)

Network architecture search of X-ray based scientific applications. - Adarsha Balaji; Ramyad Hadidi; Gregory Kollmer; Mohammed E. Fouda; Prasanna Balaprakash (CoRR, 2024)

Endor: Hardware-Friendly Sparse Format for Offloaded LLM Inference. - Donghyeon Joo; Ramyad Hadidi; Soheil Feizi; Bahar Asgari (CoRR, 2024)

La Superba: Leveraging a Self-Comparison Method to Understand the Performance Benefits of Sparse Acceleration Optimizations. - Nebil Ozer; Gregory Kollmer; Ramyad Hadidi; Bahar Asgari (ISPASS, 2025)

Mustafar: Promoting Unstructured Sparsity for KV Cache Pruning in LLM Inference. - Donghyeon Joo; Helya Hosseini; Ramyad Hadidi; Bahar Asgari (CoRR, 2025)