Efficient Algorithm Hardware Co Design

Media Summary: Dr. Vivienne Sze is an associate professor in the EECS department at MIT. Vivienne is recognized for her leading work on ... Presentation at edge ai + vision alliance: ... In this video, our research work is presented: “RAMAN: Resource-

Efficient Algorithm Hardware Co Design - Detailed Analysis & Overview

Dr. Vivienne Sze is an associate professor in the EECS department at MIT. Vivienne is recognized for her leading work on ... Presentation at edge ai + vision alliance: ... In this video, our research work is presented: “RAMAN: Resource- Abstract: As the silicon technology approaches the Post-Moore's Law Era, Webinar Archive – Now Available! In this webinar, Prof. Priyadarshini (Priya) Panda, from the Intelligent Computing Lab at Yale ... Keynote by Prof. Deming Chen, UIUC (VAST Lab Alumni) at ROAD4NN Workshop. Originally posted at ...

This talk is part of the Scientific Machine Learning Research Talks (SMaRT) Seminar Series, a joint initiative between Johns ... This is the recording of my invited online talk at the Washington DC Quantum Computing Meetup on June 7, 2026. Talk title: ... More accurate machine-learning requires larger models – but large models pose problems both in the training and inference ... Conference talk for the SC '23 paper by Wenqi Jiang, Shigang Li, Yu Zhu, Johannes de Fine Licht, Zhenhao He, Runbin Shi, ...

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Ep 13: Energy-efficient Algorithm-hardware Co-design with Dr. Vivienne Sze, MIT

Once-for-All DNNs: Simplifying Design of Efficient Models for Diverse Hardware, [Invited Talk]

RAMAN: Resource-efficient ApproxiMate Posit Processing for Algorithm–Hardware Co-desigN

Software-Hardware Codesign for Efficient In-Memory Regular Pattern Matching

Efficient Algorithm-Hardware Co-Design Methodology for Quantized LLM Acceleration

Biologically Inspired Algorithm & Hardware Co-Design | Prof. Priya Panda (Yale University)

HiPEAC 2026 keynote 3: AI and hardware co-design: Taming quality, productivity, and reliability

[EGRAPHS24] Algorithm-Aware Hardware Optimization using E-Graph Rewriting: how should we marry(…)

Elegant and Effective Co-design of Machine-Learning Algorithms and Hardware Accelerators (ROAD4NN)

Bio-Inspired Algorithm & Hardware Co-Design for Efficient AI | Dr. Priya Panda | JHU-IITD SMaRT

Machine Learning for Reliable Quantum Computing: An Algorithm–Hardware Co-Design Perspective

HiPEAC22 Keynote 1: Efficient Machine Learning: Algorithms-Hardware Co-design – Hai 'Helen' Li

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Ep 13: Energy-efficient Algorithm-hardware Co-design with Dr. Vivienne Sze, MIT

Ep 13: Energy-efficient Algorithm-hardware Co-design with Dr. Vivienne Sze, MIT

Dr. Vivienne Sze is an associate professor in the EECS department at MIT. Vivienne is recognized for her leading work on ...

Once-for-All DNNs: Simplifying Design of Efficient Models for Diverse Hardware, [Invited Talk]

Once-for-All DNNs: Simplifying Design of Efficient Models for Diverse Hardware, [Invited Talk]

Presentation at edge ai + vision alliance: ...

RAMAN: Resource-efficient ApproxiMate Posit Processing for Algorithm–Hardware Co-desigN

RAMAN: Resource-efficient ApproxiMate Posit Processing for Algorithm–Hardware Co-desigN

In this video, our research work is presented: “RAMAN: Resource-

Software-Hardware Codesign for Efficient In-Memory Regular Pattern Matching

Software-Hardware Codesign for Efficient In-Memory Regular Pattern Matching

https://pldi22.sigplan.org/details/pldi-2022-pldi/31/Software-

Efficient Algorithm-Hardware Co-Design Methodology for Quantized LLM Acceleration

Efficient Algorithm-Hardware Co-Design Methodology for Quantized LLM Acceleration

Abstract: As the silicon technology approaches the Post-Moore's Law Era,

Biologically Inspired Algorithm & Hardware Co-Design | Prof. Priya Panda (Yale University)

Biologically Inspired Algorithm & Hardware Co-Design | Prof. Priya Panda (Yale University)

Webinar Archive – Now Available! In this webinar, Prof. Priyadarshini (Priya) Panda, from the Intelligent Computing Lab at Yale ...

HiPEAC 2026 keynote 3: AI and hardware co-design: Taming quality, productivity, and reliability

HiPEAC 2026 keynote 3: AI and hardware co-design: Taming quality, productivity, and reliability

Further information: 'AI and

[EGRAPHS24] Algorithm-Aware Hardware Optimization using E-Graph Rewriting: how should we marry(…)

[EGRAPHS24] Algorithm-Aware Hardware Optimization using E-Graph Rewriting: how should we marry(…)

Algorithm

Elegant and Effective Co-design of Machine-Learning Algorithms and Hardware Accelerators (ROAD4NN)

Elegant and Effective Co-design of Machine-Learning Algorithms and Hardware Accelerators (ROAD4NN)

Keynote by Prof. Deming Chen, UIUC (VAST Lab Alumni) at ROAD4NN Workshop. Originally posted at ...

Bio-Inspired Algorithm & Hardware Co-Design for Efficient AI | Dr. Priya Panda | JHU-IITD SMaRT

Bio-Inspired Algorithm & Hardware Co-Design for Efficient AI | Dr. Priya Panda | JHU-IITD SMaRT

This talk is part of the Scientific Machine Learning Research Talks (SMaRT) Seminar Series, a joint initiative between Johns ...

Machine Learning for Reliable Quantum Computing: An Algorithm–Hardware Co-Design Perspective

Machine Learning for Reliable Quantum Computing: An Algorithm–Hardware Co-Design Perspective

This is the recording of my invited online talk at the Washington DC Quantum Computing Meetup on June 7, 2026. Talk title: ...

HiPEAC22 Keynote 1: Efficient Machine Learning: Algorithms-Hardware Co-design – Hai 'Helen' Li

HiPEAC22 Keynote 1: Efficient Machine Learning: Algorithms-Hardware Co-design – Hai 'Helen' Li

More accurate machine-learning requires larger models – but large models pose problems both in the training and inference ...

SC '23: Co-design hardware and algorithm for vector search

SC '23: Co-design hardware and algorithm for vector search

Conference talk for the SC '23 paper by Wenqi Jiang, Shigang Li, Yu Zhu, Johannes de Fine Licht, Zhenhao He, Runbin Shi, ...