Amir Yazdanbakhsh

112 papers A* 30A 2B 3C 2Misc 2Journal 59Unranked 12
YearRankTypeTitle / Venue / Authors
2026 J jnl
Magellan: Autonomous Discovery of Novel Compiler Optimization Heuristics with AlphaEvolve.
CoRR
Hongzheng Chen, Alexander Novikov, Ngân Vu, Hanna Alam, Zhiru Zhang, Aiden Grossman, Mircea Trofin, Amir Yazdanbakhsh
2026 J jnl
ParEVO: Synthesizing Code for Irregular Data: High-Performance Parallelism through Agentic Evolution.
CoRR
Liu Yang, Zeyu Nie, Andrew Liu, Felix Zou, Deniz Altinbüken, Amir Yazdanbakhsh, Quanquan C. Liu
2025 J jnl
Architecture 2.0: Foundations of Artificial Intelligence Agents for Modern Computer System Design.
Computer
Vijay Janapa Reddi, Amir Yazdanbakhsh
2025 J jnl
Automated High-Level Code Optimization for Warehouse Performance.
IEEE Micro
Alexander Shypula, Aman Madaan, Yimeng Zeng, Uri Alon, Jacob R. Gardner, Milad Hashemi, Graham Neubig, Parthasarathy Ranganathan, Osbert Bastani, Amir Yazdanbakhsh
2025 J jnl
Beyond Moore's Law: Harnessing the Redshift of Generative AI with Effective Hardware-Software Co-Design.
CoRR
Amir Yazdanbakhsh
2025 J jnl
COSMIC: Enabling Full-Stack Co-Design and Optimization of Distributed Machine Learning Systems.
CoRR
Aditi Raju, Jared Ni, William Won, Changhai Man, Srivatsan Krishnan, Srinivas Sridharan, Amir Yazdanbakhsh, Tushar Krishna, Vijay Janapa Reddi
2025 A* conf
Concorde: Fast and Accurate CPU Performance Modeling with Compositional Analytical-ML Fusion.
ISCA
Arash Nasr-Esfahany, Mohammad Alizadeh, Victor Lee, Hanna Alam, Brett W. Coon, David E. Culler, Vidushi Dadu, Martin Dixon, Henry M. Levy, Santosh Pandey, Parthasarathy Ranganathan, Amir Yazdanbakhsh
2025 J jnl
Concorde: Fast and Accurate CPU Performance Modeling with Compositional Analytical-ML Fusion.
CoRR
Arash Nasr-Esfahany, Mohammad Alizadeh, Victor Lee, Hanna Alam, Brett W. Coon, David E. Culler, Vidushi Dadu, Martin Dixon, Henry M. Levy, Santosh Pandey, Parthasarathy Ranganathan, Amir Yazdanbakhsh
2025 J jnl
ECO: An LLM-Driven Efficient Code Optimizer for Warehouse Scale Computers.
CoRR
Hannah Lin, Martin Maas, Maximilian Roquemore, Arman Hasanzadeh, Fred Lewis, Yusuf Simonson, Tzu-Wei Yang, Amir Yazdanbakhsh, Deniz Altinbüken, Florin Papa, Maggie Nolan Edmonds, Aditya Patil, Don Schwarz, Satish Chandra, Chris Kennelly, Milad Hashemi, Parthasarathy Ranganathan
2025 A* conf
Effective Interplay between Sparsity and Quantization: From Theory to Practice.
ICLR
Simla Burcu Harma, Ayan Chakraborty, Elizaveta Kostenok, Danila Mishin, Dongho Ha, Babak Falsafi, Martin Jaggi, Ming Liu, Yunho Oh, Suvinay Subramanian, Amir Yazdanbakhsh
2025 A* conf
LIA: A Single-GPU LLM Inference Acceleration with Cooperative AMX-Enabled CPU-GPU Computation and CXL Offloading.
ISCA
Hyungyo Kim, Nachuan Wang, Qirong Xia, Jinghan Huang, Amir Yazdanbakhsh, Nam Sung Kim
2025 A* conf
Learning to Keep a Promise: Scaling Language Model Decoding Parallelism with Learned Asynchronous Decoding.
ICML
Tian Jin, Ellie Y. Cheng, Zachary Ankner, Nikunj Saunshi, Blake M. Elias, Amir Yazdanbakhsh, Jonathan Ragan-Kelley, Suvinay Subramanian, Michael Carbin
2025 J jnl
Learning to Keep a Promise: Scaling Language Model Decoding Parallelism with Learned Asynchronous Decoding.
CoRR
Tian Jin, Ellie Y. Cheng, Zachary Ankner, Nikunj Saunshi, Blake M. Elias, Amir Yazdanbakhsh, Jonathan Ragan-Kelley, Suvinay Subramanian, Michael Carbin
2025 J jnl
OPTIMA: Optimal One-shot Pruning for LLMs via Quadratic Programming Reconstruction.
CoRR
Mohammad Mozaffari, Samuel Kushnir, Maryam Mehri Dehnavi, Amir Yazdanbakhsh
2025 — conf
Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers.
CPAL
Abhimanyu Rajeshkumar Bambhaniya, Amir Yazdanbakhsh, Suvinay Subramanian, Sheng-Chun Kao, Shivani Agrawal, Utku Evci, Tushar Krishna
2025 J jnl
QuArch: A Benchmark for Evaluating LLM Reasoning in Computer Architecture.
CoRR
Shvetank Prakash, Andrew Cheng, Arya Tschand, Mark Mazumder, Varun Gohil, Jeffrey Jian Ma, Jason Yik, Zishen Wan, Jessica Quaye, Elisavet Lydia Alvanaki, Avinash Kumar, Chandrashis Mazumdar, Tuhin Khare, Alexander Ingare, Ikechukwu Uchendu, Radhika Ghosal, Abhishek Tyagi, Chenyu Wang, Andrea Mattia Garavagno, Sarah Gu, Alice Guo, Grace Hur, Luca P. Carloni, Tushar Krishna, Ankita Nayak, Amir Yazdanbakhsh, Vijay Janapa Reddi
2025 J jnl
QuArch: A Question-Answering Dataset for AI Agents in Computer Architecture.
IEEE Comput. Archit. Lett.
Shvetank Prakash, Andrew Cheng, Jason Yik, Arya Tschand, Radhika Ghosal, Ikechukwu Uchendu, Jessica Quaye, Jeffrey Jian Ma, Shreyas Grampurohit, Sofia Giannuzzi, Arnav Balyan, Fin Amin, Aadya Pipersenia, Yash Choudhary, Ankita Nayak, Amir Yazdanbakhsh, Vijay Janapa Reddi
2025 J jnl
QuArch: A Question-Answering Dataset for AI Agents in Computer Architecture.
CoRR
Shvetank Prakash, Andrew Cheng, Jason Yik, Arya Tschand, Radhika Ghosal, Ikechukwu Uchendu, Jessica Quaye, Jeffrey Jian Ma, Shreyas Grampurohit, Sofia Giannuzzi, Arnav Balyan, Fin Amin, Aadya Pipersenia, Yash Choudhary, Ankita Nayak, Amir Yazdanbakhsh, Vijay Janapa Reddi
2025 A* conf
RAGO: Systematic Performance Optimization for Retrieval-Augmented Generation Serving.
ISCA
Wenqi Jiang, Suvinay Subramanian, Cat Graves, Gustavo Alonso, Amir Yazdanbakhsh, Vidushi Dadu
2025 J jnl
RAGO: Systematic Performance Optimization for Retrieval-Augmented Generation Serving.
CoRR
Wenqi Jiang, Suvinay Subramanian, Cat Graves, Gustavo Alonso, Amir Yazdanbakhsh, Vidushi Dadu
2025 A* conf
SLiM: One-shot Quantization and Sparsity with Low-rank Approximation for LLM Weight Compression.
ICML
Mohammad Mozaffari, Amir Yazdanbakhsh, Maryam Mehri Dehnavi
2025 A* conf
SLoPe: Double-Pruned Sparse Plus Lazy Low-Rank Adapter Pretraining of LLMs.
ICLR
Mohammad Mozaffari, Amir Yazdanbakhsh, Zhao Zhang, Maryam Mehri Dehnavi
2025 J jnl
SWE-fficiency: Can Language Models Optimize Real-World Repositories on Real Workloads?
CoRR
Jeffrey Jian Ma, Milad Hashemi, Amir Yazdanbakhsh, Kevin Swersky, Ofir Press, Enhui Li, Vijay Janapa Reddi, Parthasarathy Ranganathan
2025 A* conf
SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity.
ICML
Samir Khaki, Xiuyu Li, Junxian Guo, Ligeng Zhu, Konstantinos N. Plataniotis, Amir Yazdanbakhsh, Kurt Keutzer, Song Han, Zhijian Liu
2025 J jnl
SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity.
CoRR
Samir Khaki, Xiuyu Li, Junxian Guo, Ligeng Zhu, Chenfeng Xu, Konstantinos N. Plataniotis, Amir Yazdanbakhsh, Kurt Keutzer, Song Han, Zhijian Liu
2025 A* conf
The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws.
ICLR
Tian Jin, Ahmed Imtiaz Humayun, Utku Evci, Suvinay Subramanian, Amir Yazdanbakhsh, Dan Alistarh, Gintare Karolina Dziugaite
2025 J jnl
The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws.
CoRR
Tian Jin, Ahmed Imtiaz Humayun, Utku Evci, Suvinay Subramanian, Amir Yazdanbakhsh, Dan Alistarh, Gintare Karolina Dziugaite
2025 J jnl
Understanding and Optimizing Multi-Stage AI Inference Pipelines.
CoRR
Abhimanyu Rajeshkumar Bambhaniya, Hanjiang Wu, Suvinay Subramanian, Sudarshan Srinivasan, Souvik Kundu, Amir Yazdanbakhsh, Midhilesh Elavazhagan, Madhu Kumar, Tushar Krishna
2024 A* conf
CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming.
NeurIPS
Ali TehraniJamsaz, Arijit Bhattacharjee, Le Chen, Nesreen K. Ahmed, Amir Yazdanbakhsh, Ali Jannesari
2024 J jnl
CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming.
CoRR
Ali TehraniJamsaz, Arijit Bhattacharjee, Le Chen, Nesreen K. Ahmed, Amir Yazdanbakhsh, Ali Jannesari
2024 A* conf
DACAPO: Accelerating Continuous Learning in Autonomous Systems for Video Analytics.
ISCA
Yoonsung Kim, Changhun Oh, Jinwoo Hwang, Wonung Kim, Seongryong Oh, Yubin Lee, Hardik Sharma, Amir Yazdanbakhsh, Jongse Park
2024 J jnl
DaCapo: Accelerating Continuous Learning in Autonomous Systems for Video Analytics.
CoRR
Yoonsung Kim, Changhun Oh, Jinwoo Hwang, Wonung Kim, Seongryong Oh, Yubin Lee, Hardik Sharma, Amir Yazdanbakhsh, Jongse Park
2024 J jnl
Effective Interplay between Sparsity and Quantization: From Theory to Practice.
CoRR
Simla Burcu Harma, Ayan Chakraborty, Elizaveta Kostenok, Danila Mishin, Dongho Ha, Babak Falsafi, Martin Jaggi, Ming Liu, Yunho Oh, Suvinay Subramanian, Amir Yazdanbakhsh
2024 J jnl
Exploiting Intel Advanced Matrix Extensions (AMX) for Large Language Model Inference.
IEEE Comput. Archit. Lett.
Hyungyo Kim, Gaohan Ye, Nachuan Wang, Amir Yazdanbakhsh, Nam Sung Kim
2024 — conf
In-Storage Domain-Specific Acceleration for Serverless Computing.
ASPLOS (2)
Rohan Mahapatra, Soroush Ghodrati, Byung Hoon Ahn, Sean Kinzer, Shu-Ting Wang, Hanyang Xu, Lavanya Karthikeyan, Hardik Sharma, Amir Yazdanbakhsh, Mohammad Alian, Hadi Esmaeilzadeh
2024 — conf
Jaxpruner: A Concise Library for Sparsity Research.
CPAL
Joo Hyung Lee, Wonpyo Park, Nicole Mitchell, Jonathan Pilault, Johan Samir Obando Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Woohyun Han, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart J. C. Bik, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann N. Dauphin, Gintare Karolina Dziugaite, Pablo Samuel Castro, Utku Evci
2024 A* conf
Learning Performance-Improving Code Edits.
ICLR
Alexander Shypula, Aman Madaan, Yimeng Zeng, Uri Alon, Jacob R. Gardner, Yiming Yang, Milad Hashemi, Graham Neubig, Parthasarathy Ranganathan, Osbert Bastani, Amir Yazdanbakhsh
2024 J jnl
Progressive Gradient Flow for Robust N: M Sparsity Training in Transformers.
CoRR
Abhimanyu Rajeshkumar Bambhaniya, Amir Yazdanbakhsh, Suvinay Subramanian, Sheng-Chun Kao, Shivani Agrawal, Utku Evci, Tushar Krishna
2024 J jnl
SLoPe: Double-Pruned Sparse Plus Lazy Low-Rank Adapter Pretraining of LLMs.
CoRR
Mohammad Mozaffari, Amir Yazdanbakhsh, Zhao Zhang, Maryam Mehri Dehnavi
2024 A* conf
ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization.
NeurIPS
Haoran You, Yipin Guo, Yichao Fu, Wei Zhou, Huihong Shi, Xiaofan Zhang, Souvik Kundu, Amir Yazdanbakhsh, Yingyan (Celine) Lin
2024 J jnl
ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization.
CoRR
Haoran You, Yipin Guo, Yichao Fu, Wei Zhou, Huihong Shi, Xiaofan Zhang, Souvik Kundu, Amir Yazdanbakhsh, Yingyan Lin
2024 — conf
TAO: Re-Thinking DL-based Microarchitecture Simulation.
SIGMETRICS/Performance (Abstracts)
Santosh Pandey, Amir Yazdanbakhsh, Hang Liu
2024 J jnl
TAO: Re-Thinking DL-based Microarchitecture Simulation.
Proc. ACM Meas. Anal. Comput. Syst.
Santosh Pandey, Amir Yazdanbakhsh, Hang Liu
2024 — conf
Tandem Processor: Grappling with Emerging Operators in Neural Networks.
ASPLOS (2)
Soroush Ghodrati, Sean Kinzer, Hanyang Xu, Rohan Mahapatra, Yoonsung Kim, Byung Hoon Ahn, Dong Kai Wang, Lavanya Karthikeyan, Amir Yazdanbakhsh, Jongse Park, Nam Sung Kim, Hadi Esmaeilzadeh
2024 J jnl
Tao: Re-Thinking DL-based Microarchitecture Simulation.
CoRR
Santosh Pandey, Amir Yazdanbakhsh, Hang Liu
2024 Misc conf
USM-Lite: Quantization and Sparsity Aware Fine-Tuning for Speech Recognition with Universal Speech Models.
ICASSP
Shaojin Ding, David Qiu, David Rim, Yanzhang He, Oleg Rybakov, Bo Li, Rohit Prabhavalkar, Weiran Wang, Tara N. Sainath, Zhonglin Han, Jian Li, Amir Yazdanbakhsh, Shivani Agrawal
2024 A* conf
When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models.
ICML
Haoran You, Yichao Fu, Zheng Wang, Amir Yazdanbakhsh, Yingyan Celine Lin
2024 J jnl
When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models.
CoRR
Haoran You, Yichao Fu, Zheng Wang, Amir Yazdanbakhsh, Yingyan Lin
2023 A* conf
ArchGym: An Open-Source Gymnasium for Machine Learning Assisted Architecture Design.
ISCA
Srivatsan Krishnan, Amir Yazdanbakhsh, Shvetank Prakash, Jason Jabbour, Ikechukwu Uchendu, Susobhan Ghosh, Behzad Boroujerdian, Daniel Richins, Devashree Tripathy, Aleksandra Faust, Vijay Janapa Reddi
2023 J jnl
ArchGym: An Open-Source Gymnasium for Machine Learning Assisted Architecture Design.
CoRR
Srivatsan Krishnan, Amir Yazdanbakhsh, Shvetank Prakash, Jason Jabbour, Ikechukwu Uchendu, Susobhan Ghosh, Behzad Boroujerdian, Daniel Richins, Devashree Tripathy, Aleksandra Faust, Vijay Janapa Reddi
2023 A* conf
Architecture 2.0: Challenges and Opportunities.
DAC
Vijay Janapa Reddi, Amir Yazdanbakhsh
2023 J jnl
Domain-Specific Computational Storage for Serverless Computing.
CoRR
Rohan Mahapatra, Soroush Ghodrati, Byung Hoon Ahn, Sean Kinzer, Shu-Ting Wang, Hanyang Xu, Lavanya Karthikeyan, Hardik Sharma, Amir Yazdanbakhsh, Mohammad Alian, Hadi Esmaeilzadeh
2023 — conf
FLAT: An Optimized Dataflow for Mitigating Attention Bottlenecks.
ASPLOS (2)
Sheng-Chun Kao, Suvinay Subramanian, Gaurav Agrawal, Amir Yazdanbakhsh, Tushar Krishna
2023 J jnl
JaxPruner: A concise library for sparsity research.
CoRR
Joo Hyung Lee, Wonpyo Park, Nicole Mitchell, Jonathan Pilault, Johan S. Obando-Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart J. C. Bik, Woohyun Han, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann N. Dauphin, Karolina Dziugaite, Pablo Samuel Castro, Utku Evci
2023 J jnl
Learning Performance-Improving Code Edits.
CoRR
Aman Madaan, Alexander Shypula, Uri Alon, Milad Hashemi, Parthasarathy Ranganathan, Yiming Yang, Graham Neubig, Amir Yazdanbakhsh
2023 A* conf
MESA: Microarchitecture Extensions for Spatial Architecture Generation.
ISCA
Dong Kai Wang, Jiaqi Lou, Naiyin Jin, Edwin Mascarenhas, Rohan Mahapatra, Sean Kinzer, Soroush Ghodrati, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Nam Sung Kim
2023 A* conf
STEP: Learning N: M Structured Sparsity Masks from Scratch with Precondition.
ICML
Yucheng Lu, Shivani Agrawal, Suvinay Subramanian, Oleg Rybakov, Christopher De Sa, Amir Yazdanbakhsh
2023 J jnl
STEP: Learning N: M Structured Sparsity Masks from Scratch with Precondition.
CoRR
Yucheng Lu, Shivani Agrawal, Suvinay Subramanian, Oleg Rybakov, Christopher De Sa, Amir Yazdanbakhsh
2023 A* conf
Self-Refine: Iterative Refinement with Self-Feedback.
NeurIPS
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, Peter Clark
2023 J jnl
Self-Refine: Iterative Refinement with Self-Feedback.
CoRR
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Sean Welleck, Bodhisattwa Prasad Majumder, Shashank Gupta, Amir Yazdanbakhsh, Peter Clark
2023 J jnl
USM-Lite: Quantization and Sparsity Aware Fine-tuning for Speech Recognition with Universal Speech Models.
CoRR
Shaojin Ding, David Qiu, David Rim, Yanzhang He, Oleg Rybakov, Bo Li, Rohit Prabhavalkar, Weiran Wang, Tara N. Sainath, Shivani Agrawal, Zhonglin Han, Jian Li, Amir Yazdanbakhsh
2023 — conf
What Makes Chain-of-Thought Prompting Effective? A Counterfactual Study.
EMNLP (Findings)
Aman Madaan, Katherine Hermann, Amir Yazdanbakhsh
2022 J jnl
Accelerating Attention through Gradient-Based Learned Runtime Pruning.
CoRR
Zheng Li, Soroush Ghodrati, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Mingu Kang
2022 A* conf
Accelerating attention through gradient-based learned runtime pruning.
ISCA
Zheng Li, Soroush Ghodrati, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Mingu Kang
2022 — conf
An Evaluation of Edge TPU Accelerators for Convolutional Neural Networks.
IISWC
Kiran Seshadri, Berkin Akin, James Laudon, Ravi Narayanaswami, Amir Yazdanbakhsh
2022 A* conf
Data-Driven Offline Optimization for Architecting Hardware Accelerators.
ICLR
Aviral Kumar, Amir Yazdanbakhsh, Milad Hashemi, Kevin Swersky, Sergey Levine
2022 — conf
GRANITE: A Graph Neural Network Model for Basic Block Throughput Estimation.
IISWC
Ondrej Sýkora, Phitchaya Mangpo Phothilimthana, Charith Mendis, Amir Yazdanbakhsh
2022 J jnl
GRANITE: A Graph Neural Network Model for Basic Block Throughput Estimation.
CoRR
Ondrej Sýkora, Phitchaya Mangpo Phothilimthana, Charith Mendis, Amir Yazdanbakhsh
2022 A* conf
Sparse Attention Acceleration with Synergistic In-Memory Pruning and On-Chip Recomputation.
MICRO
Amir Yazdanbakhsh, Ashkan Moradifirouzabadi, Zheng Li, Mingu Kang
2022 J jnl
Sparse Attention Acceleration with Synergistic In-Memory Pruning and On-Chip Recomputation.
CoRR
Amir Yazdanbakhsh, Ashkan Moradifirouzabadi, Zheng Li, Mingu Kang
2022 J jnl
Text and Patterns: For Effective Chain of Thought, It Takes Two to Tango.
CoRR
Aman Madaan, Amir Yazdanbakhsh
2022 — conf
Towards the Co-design of Neural Networks and Accelerators.
MLSys
Yanqi Zhou, Xuanyi Dong, Tianjian Meng, Mingxing Tan, Berkin Akin, Daiyi Peng, Amir Yazdanbakhsh, Da Huang, Ravi Narayanaswami, James Laudon
2022 J jnl
Training Recipe for N: M Structured Sparsity with Decaying Pruning Mask.
CoRR
Sheng-Chun Kao, Amir Yazdanbakhsh, Suvinay Subramanian, Shivani Agrawal, Utku Evci, Tushar Krishna
2021 J jnl
An Evaluation of Edge TPU Accelerators for Convolutional Neural Networks.
CoRR
Amir Yazdanbakhsh, Kiran Seshadri, Berkin Akin, James Laudon, Ravi Narayanaswami
2021 J jnl
Apollo: Transferable Architecture Exploration.
CoRR
Amir Yazdanbakhsh, Christof Angermüller, Berkin Akin, Yanqi Zhou, Albin Jones, Milad Hashemi, Kevin Swersky, Satrajit Chatterjee, Ravi Narayanaswami, James Laudon
2021 J jnl
Data-Driven Offline Optimization For Architecting Hardware Accelerators.
CoRR
Aviral Kumar, Amir Yazdanbakhsh, Milad Hashemi, Kevin Swersky, Sergey Levine
2021 J jnl
Rethinking Co-design of Neural Architectures and Hardware Accelerators.
CoRR
Yanqi Zhou, Xuanyi Dong, Berkin Akin, Mingxing Tan, Daiyi Peng, Tianjian Meng, Amir Yazdanbakhsh, Da Huang, Ravi Narayanaswami, James Laudon
2020 A* conf
Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation.
ICLR
Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh
2020 J jnl
Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation.
CoRR
Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh
2020 B conf
Mixed-Signal Charge-Domain Acceleration of Deep Neural Networks through Interleaved Bit-Partitioned Arithmetic.
PACT
Soroush Ghodrati, Hardik Sharma, Sean Kinzer, Amir Yazdanbakhsh, Jongse Park, Nam Sung Kim, Doug Burger, Hadi Esmaeilzadeh
2020 J jnl
ReLeQ : A Reinforcement Learning Approach for Automatic Deep Quantization of Neural Networks.
IEEE Micro
Ahmed T. Elthakeb, Prannoy Pilligundla, Fatemehsadat Mireshghallah, Amir Yazdanbakhsh, Hadi Esmaeilzadeh
2019 A* conf
AxMemo: hardware-compiler co-design for approximate code memoization.
ISCA
Zhenhong Liu, Amir Yazdanbakhsh, Dong Kai Wang, Hadi Esmaeilzadeh, Nam Sung Kim
2019 J jnl
Mixed-Signal Charge-Domain Acceleration of Deep Neural networks through Interleaved Bit-Partitioned Arithmetic.
CoRR
Soroush Ghodrati, Hardik Sharma, Sean Kinzer, Amir Yazdanbakhsh, Kambiz Samadi, Nam Sung Kim, Doug Burger, Hadi Esmaeilzadeh
2019 — ch.
Towards Breaking the Memory Bandwidth Wall Using Approximate Value Prediction.
Approximate Circuits
Amir Yazdanbakhsh, Gennady Pekhimenko, Hadi Esmaeilzadeh, Onur Mutlu, Todd C. Mowry
2018 Misc conf
FlexiGAN: An End-to-End Solution for FPGA Acceleration of Generative Adversarial Networks.
FCCM
Amir Yazdanbakhsh, Michael Brzozowski, Behnam Khaleghi, Soroush Ghodrati, Kambiz Samadi, Nam Sung Kim, Hadi Esmaeilzadeh
2018 A* conf
GANAX: A Unified MIMD-SIMD Acceleration for Generative Adversarial Networks.
ISCA
Amir Yazdanbakhsh, Kambiz Samadi, Nam Sung Kim, Hadi Esmaeilzadeh
2018 J jnl
GANAX: A Unified MIMD-SIMD Acceleration for Generative Adversarial Networks.
CoRR
Amir Yazdanbakhsh, Hajar Falahati, Philip J. Wolfe, Kambiz Samadi, Nam Sung Kim, Hadi Esmaeilzadeh
2018 B conf
In-DRAM near-data approximate acceleration for GPUs.
PACT
Amir Yazdanbakhsh, Choungki Song, Jacob Sacks, Pejman Lotfi-Kamran, Hadi Esmaeilzadeh, Nam Sung Kim
2018 — —
Neuro-general computing an acceleration-approximation approach.
Amir Yazdanbakhsh
2018 J jnl
ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural Networks.
CoRR
Ahmed T. Elthakeb, Prannoy Pilligundla, Amir Yazdanbakhsh, Sean Kinzer, Hadi Esmaeilzadeh
2018 J jnl
SiMul: An Algorithm-Driven Approximate Multiplier Design for Machine Learning.
IEEE Micro
Zhenhong Liu, Amir Yazdanbakhsh, Taejoon Park, Hadi Esmaeilzadeh, Nam Sung Kim
2018 A* conf
SnaPEA: Predictive Early Activation for Reducing Computation in Deep Convolutional Neural Networks.
ISCA
Vahideh Akhlaghi, Amir Yazdanbakhsh, Kambiz Samadi, Rajesh K. Gupta, Hadi Esmaeilzadeh
2017 J jnl
AxBench: A Multiplatform Benchmark Suite for Approximate Computing.
IEEE Des. Test
Amir Yazdanbakhsh, Divya Mahajan, Hadi Esmaeilzadeh, Pejman Lotfi-Kamran
2016 A conf
Grater: An approximation workflow for exploiting data-level parallelism in FPGA acceleration.
DATE
Atieh Lotfi, Abbas Rahimi, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Rajesh K. Gupta
2016 J jnl
Mitigating the Memory Bottleneck With Approximate Load Value Prediction.
IEEE Des. Test
Amir Yazdanbakhsh, Bradley Thwaites, Hadi Esmaeilzadeh, Gennady Pekhimenko, Onur Mutlu, Todd C. Mowry
2016 J jnl
RFVP: Rollback-Free Value Prediction with Safe-to-Approximate Loads.
ACM Trans. Archit. Code Optim.
Amir Yazdanbakhsh, Gennady Pekhimenko, Bradley Thwaites, Hadi Esmaeilzadeh, Onur Mutlu, Todd C. Mowry
2016 A* conf
TABLA: A unified template-based framework for accelerating statistical machine learning.
HPCA
Divya Mahajan, Jongse Park, Emmanuel Amaro, Hardik Sharma, Amir Yazdanbakhsh, Joon Kyung Kim, Hadi Esmaeilzadeh
2016 A* conf
Towards Statistical Guarantees in Controlling Quality Tradeoffs for Approximate Acceleration.
ISCA
Divya Mahajan, Amir Yazdanbakhsh, Jongse Park, Bradley Thwaites, Hadi Esmaeilzadeh
2015 J jnl
Axilog: Abstractions for Approximate Hardware Design and Reuse.
IEEE Micro
Divya Mahajan, Kartik Ramkrishnan, Rudra Jariwala, Amir Yazdanbakhsh, Jongse Park, Bradley Thwaites, Anandhavel Nagendrakumar, Abbas Rahimi, Hadi Esmaeilzadeh, Kia Bazargan
2015 A conf
Axilog: language support for approximate hardware design.
DATE
Amir Yazdanbakhsh, Divya Mahajan, Bradley Thwaites, Jongse Park, Anandhavel Nagendrakumar, Sindhuja Sethuraman, Kartik Ramkrishnan, Nishanthi Ravindran, Rudra Jariwala, Abbas Rahimi, Hadi Esmaeilzadeh, Kia Bazargan
2015 J jnl
Comprehensive Circuit Failure Prediction for Logic and SRAM Using Virtual Aging.
IEEE Micro
Amir Yazdanbakhsh, Raghuraman Balasubramanian, Tony Nowatzki, Karthikeyan Sankaralingam
2015 A* conf
Neural acceleration for GPU throughput processors.
MICRO
Amir Yazdanbakhsh, Jongse Park, Hardik Sharma, Pejman Lotfi-Kamran, Hadi Esmaeilzadeh
2015 — conf
Online and Operand-Aware Detection of Failures Utilizing False Alarm Vectors.
ACM Great Lakes Symposium on VLSI
Amir Yazdanbakhsh, David J. Palframan, Azadeh Davoodi, Nam Sung Kim, Mikko H. Lipasti
2014 J jnl
Customized pipeline and instruction set architecture for embedded processing engines.
J. Supercomput.
Amir Yazdanbakhsh, Mostafa E. Salehi, Sied Mehdi Fakhraie
2014 A* conf
General-purpose code acceleration with limited-precision analog computation.
ISCA
Renée St. Amant, Amir Yazdanbakhsh, Jongse Park, Bradley Thwaites, Hadi Esmaeilzadeh, Arjang Hassibi, Luis Ceze, Doug Burger
2014 J jnl
Implementation-aware selection of the custom instruction set for extensible processors.
Microprocess. Microsystems
Amir Yazdanbakhsh, Mehdi Kamal, Sied Mehdi Fakhraie, Ali Afzali-Kusha, Saeed Safari, Massoud Pedram
2014 B conf
Rollback-free value prediction with approximate loads.
PACT
Bradley Thwaites, Gennady Pekhimenko, Hadi Esmaeilzadeh, Amir Yazdanbakhsh, Onur Mutlu, Jongse Park, Girish Mururu, Todd C. Mowry
2013 J jnl
A new merit function for custom instruction selection under an area budget constraint.
Des. Autom. Embed. Syst.
Mehdi Kamal, Amir Yazdanbakhsh, Hamid Noori, Ali Afzali-Kusha, Massoud Pedram
2012 J jnl
Instruction set architectural guidelines for embedded packet-processing engines.
J. Syst. Archit.
Mostafa E. Salehi, Sied Mehdi Fakhraie, Amir Yazdanbakhsh
2011 C conf
Dynamic Soft Error Hardening via Joint Body Biasing and Dynamic Voltage Scaling.
DSD
Farshad Firouzi, Amir Yazdanbakhsh, Hamed Dorosti, Sied Mehdi Fakhraie
2010 — conf
Energy-aware design space exploration of registerfile for extensible processors.
ICSAMOS
Amir Yazdanbakhsh, Mehdi Kamal, Mostafa E. Salehi, Hamid Noori, Sied Mehdi Fakhraie
2010 C conf
Instruction reliability analysis for embedded processors.
DDECS
Ali Azarpeyvand, Mostafa E. Salehi, Farshad Firouzi, Amir Yazdanbakhsh, Sied Mehdi Fakhraie