Amir Yazdanbakhsh

Orcid: 0000-0001-8199-7671

Affiliations:

Google

According to our database¹, Amir Yazdanbakhsh authored at least 67 papers between 2010 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

Legend:

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In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

TAO: Re-Thinking DL-based Microarchitecture Simulation.

[BibT_eX]

[DOI]

Santosh Pandey

Amir Yazdanbakhsh

Hang Liu

Proc. ACM Meas. Anal. Comput. Syst., 2024

ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization.

[BibT_eX]

[DOI]

CoRR, 2024

Effective Interplay between Sparsity and Quantization: From Theory to Practice.

[BibT_eX]

[DOI]

CoRR, 2024

SLoPe: Double-Pruned Sparse Plus Lazy Low-Rank Adapter Pretraining of LLMs.

[BibT_eX]

[DOI]

CoRR, 2024

Progressive Gradient Flow for Robust N: M Sparsity Training in Transformers.

[BibT_eX]

[DOI]

Abhimanyu Rajeshkumar Bambhaniya

CoRR, 2024

Exploiting Intel Advanced Matrix Extensions (AMX) for Large Language Model Inference.

[BibT_eX]

[DOI]

IEEE Comput. Archit. Lett., 2024

DACAPO: Accelerating Continuous Learning in Autonomous Systems for Video Analytics.

[BibT_eX]

[DOI]

Proceedings of the 51st ACM/IEEE Annual International Symposium on Computer Architecture, 2024

When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning Performance-Improving Code Edits.

[BibT_eX]

[DOI]

Parthasarathy Ranganathan

Osbert Bastani

Amir Yazdanbakhsh

Proceedings of the Twelfth International Conference on Learning Representations, 2024

USM-Lite: Quantization and Sparsity Aware Fine-Tuning for Speech Recognition with Universal Speech Models.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2024

In-Storage Domain-Specific Acceleration for Serverless Computing.

[BibT_eX]

[DOI]

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

Tandem Processor: Grappling with Emerging Operators in Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

2023

JaxPruner: A concise library for sparsity research.

[BibT_eX]

[DOI]

CoRR, 2023

Self-Refine: Iterative Refinement with Self-Feedback.

[BibT_eX]

[DOI]

Bodhisattwa Prasad Majumder

Shashank Gupta

Amir Yazdanbakhsh

Peter Clark

CoRR, 2023

Domain-Specific Computational Storage for Serverless Computing.

[BibT_eX]

[DOI]

CoRR, 2023

Learning Performance-Improving Code Edits.

[BibT_eX]

[DOI]

Parthasarathy Ranganathan

Yiming Yang

Graham Neubig

Amir Yazdanbakhsh

CoRR, 2023

Self-Refine: Iterative Refinement with Self-Feedback.

[BibT_eX]

[DOI]

Bodhisattwa Prasad Majumder

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

MESA: Microarchitecture Extensions for Spatial Architecture Generation.

[BibT_eX]

[DOI]

Proceedings of the 50th Annual International Symposium on Computer Architecture, 2023

ArchGym: An Open-Source Gymnasium for Machine Learning Assisted Architecture Design.

[BibT_eX]

[DOI]

Proceedings of the 50th Annual International Symposium on Computer Architecture, 2023

STEP: Learning N: M Structured Sparsity Masks from Scratch with Precondition.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

What Makes Chain-of-Thought Prompting Effective? A Counterfactual Study.

[BibT_eX]

[DOI]

Aman Madaan

Katherine Hermann

Amir Yazdanbakhsh

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Architecture 2.0: Challenges and Opportunities.

[BibT_eX]

[DOI]

Vijay Janapa Reddi

Amir Yazdanbakhsh

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

FLAT: An Optimized Dataflow for Mitigating Attention Bottlenecks.

[BibT_eX]

[DOI]

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023

2022

Text and Patterns: For Effective Chain of Thought, It Takes Two to Tango.

[BibT_eX]

[DOI]

Aman Madaan

Amir Yazdanbakhsh

CoRR, 2022

Training Recipe for N: M Structured Sparsity with Decaying Pruning Mask.

[BibT_eX]

[DOI]

CoRR, 2022

Towards the Co-design of Neural Networks and Accelerators.

[BibT_eX]

[DOI]

Proceedings of the Fifth Conference on Machine Learning and Systems, 2022

Sparse Attention Acceleration with Synergistic In-Memory Pruning and On-Chip Recomputation.

[BibT_eX]

[DOI]

Amir Yazdanbakhsh

Ashkan Moradifirouzabadi

Zheng Li

Mingu Kang

Proceedings of the 55th IEEE/ACM International Symposium on Microarchitecture, 2022

Accelerating attention through gradient-based learned runtime pruning.

[BibT_eX]

[DOI]

Proceedings of the ISCA '22: The 49th Annual International Symposium on Computer Architecture, New York, New York, USA, June 18, 2022

GRANITE: A Graph Neural Network Model for Basic Block Throughput Estimation.

[BibT_eX]

[DOI]

Ondrej Sýkora

Phitchaya Mangpo Phothilimthana

Charith Mendis

Amir Yazdanbakhsh

Proceedings of the IEEE International Symposium on Workload Characterization, 2022

An Evaluation of Edge TPU Accelerators for Convolutional Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Workload Characterization, 2022

Data-Driven Offline Optimization for Architecting Hardware Accelerators.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Rethinking Co-design of Neural Architectures and Hardware Accelerators.

[BibT_eX]

[DOI]

CoRR, 2021

Apollo: Transferable Architecture Exploration.

[BibT_eX]

[DOI]

CoRR, 2021

2020

ReLeQ : A Reinforcement Learning Approach for Automatic Deep Quantization of Neural Networks.

[BibT_eX]

[DOI]

Ahmed T. Elthakeb

Prannoy Pilligundla

Fatemehsadat Mireshghallah

Amir Yazdanbakhsh

Hadi Esmaeilzadeh

IEEE Micro, 2020

Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Mixed-Signal Charge-Domain Acceleration of Deep Neural Networks through Interleaved Bit-Partitioned Arithmetic.

[BibT_eX]

[DOI]

Proceedings of the PACT '20: International Conference on Parallel Architectures and Compilation Techniques, 2020

2019

Mixed-Signal Charge-Domain Acceleration of Deep Neural networks through Interleaved Bit-Partitioned Arithmetic.

[BibT_eX]

[DOI]

CoRR, 2019

AxMemo: hardware-compiler co-design for approximate code memoization.

[BibT_eX]

[DOI]

Proceedings of the 46th International Symposium on Computer Architecture, 2019

Towards Breaking the Memory Bandwidth Wall Using Approximate Value Prediction.

[BibT_eX]

[DOI]

Proceedings of the Approximate Circuits, Methodologies and CAD., 2019

2018

Neuro-general computing an acceleration-approximation approach.

[BibT_eX]

[DOI]

Amir Yazdanbakhsh

PhD thesis, 2018

SiMul: An Algorithm-Driven Approximate Multiplier Design for Machine Learning.

[BibT_eX]

[DOI]

IEEE Micro, 2018

ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2018

GANAX: A Unified MIMD-SIMD Acceleration for Generative Adversarial Networks.

[BibT_eX]

[DOI]

CoRR, 2018

GANAX: A Unified MIMD-SIMD Acceleration for Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the 45th ACM/IEEE Annual International Symposium on Computer Architecture, 2018

SnaPEA: Predictive Early Activation for Reducing Computation in Deep Convolutional Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 45th ACM/IEEE Annual International Symposium on Computer Architecture, 2018

FlexiGAN: An End-to-End Solution for FPGA Acceleration of Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the 26th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2018

In-DRAM near-data approximate acceleration for GPUs.

[BibT_eX]

[DOI]

Proceedings of the 27th International Conference on Parallel Architectures and Compilation Techniques, 2018

2017

AxBench: A Multiplatform Benchmark Suite for Approximate Computing.

[BibT_eX]

[DOI]

IEEE Des. Test, 2017

2016

RFVP: Rollback-Free Value Prediction with Safe-to-Approximate Loads.

[BibT_eX]

[DOI]

ACM Trans. Archit. Code Optim., 2016

Mitigating the Memory Bottleneck With Approximate Load Value Prediction.

[BibT_eX]

[DOI]

IEEE Des. Test, 2016

Towards Statistical Guarantees in Controlling Quality Tradeoffs for Approximate Acceleration.

[BibT_eX]

[DOI]

Proceedings of the 43rd ACM/IEEE Annual International Symposium on Computer Architecture, 2016

TABLA: A unified template-based framework for accelerating statistical machine learning.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE International Symposium on High Performance Computer Architecture, 2016

Grater: An approximation workflow for exploiting data-level parallelism in FPGA acceleration.

[BibT_eX]

[DOI]

Proceedings of the 2016 Design, Automation & Test in Europe Conference & Exhibition, 2016

2015

Comprehensive Circuit Failure Prediction for Logic and SRAM Using Virtual Aging.

[BibT_eX]

[DOI]

Amir Yazdanbakhsh

Raghuraman Balasubramanian

Tony Nowatzki

Karthikeyan Sankaralingam

IEEE Micro, 2015

Axilog: Abstractions for Approximate Hardware Design and Reuse.

[BibT_eX]

[DOI]

Anandhavel Nagendrakumar

Abbas Rahimi

Hadi Esmaeilzadeh

Kia Bazargan

IEEE Micro, 2015

Neural acceleration for GPU throughput processors.

[BibT_eX]

[DOI]

Proceedings of the 48th International Symposium on Microarchitecture, 2015

Online and Operand-Aware Detection of Failures Utilizing False Alarm Vectors.

[BibT_eX]

[DOI]

Proceedings of the 25th edition on Great Lakes Symposium on VLSI, GLVLSI 2015, Pittsburgh, PA, USA, May 20, 2015

Axilog: language support for approximate hardware design.

[BibT_eX]

[DOI]

Anandhavel Nagendrakumar

Proceedings of the 2015 Design, Automation & Test in Europe Conference & Exhibition, 2015

2014

Customized pipeline and instruction set architecture for embedded processing engines.

[BibT_eX]

[DOI]

Amir Yazdanbakhsh

Mostafa E. Salehi

Sied Mehdi Fakhraie

J. Supercomput., 2014

Implementation-aware selection of the custom instruction set for extensible processors.

[BibT_eX]

[DOI]

Microprocess. Microsystems, 2014

General-purpose code acceleration with limited-precision analog computation.

[BibT_eX]

[DOI]

Proceedings of the ACM/IEEE 41st International Symposium on Computer Architecture, 2014

Rollback-free value prediction with approximate loads.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Parallel Architectures and Compilation, 2014

2013

A new merit function for custom instruction selection under an area budget constraint.

[BibT_eX]

[DOI]

Des. Autom. Embed. Syst., 2013

2012

Instruction set architectural guidelines for embedded packet-processing engines.

[BibT_eX]

[DOI]

Mostafa E. Salehi

Sied Mehdi Fakhraie

Amir Yazdanbakhsh

J. Syst. Archit., 2012

2011

Dynamic Soft Error Hardening via Joint Body Biasing and Dynamic Voltage Scaling.

[BibT_eX]

[DOI]

Proceedings of the 14th Euromicro Conference on Digital System Design, 2011

2010

Energy-aware design space exploration of registerfile for extensible processors.

[BibT_eX]

[DOI]

Proceedings of the 2010 International Conference on Embedded Computer Systems: Architectures, 2010

Instruction reliability analysis for embedded processors.

[BibT_eX]

[DOI]

Proceedings of the 13th IEEE International Symposium on Design and Diagnostics of Electronic Circuits and Systems, 2010

Amir Yazdanbakhsh

Timeline

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