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content/members/Junyu Yin/_index.md

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@@ -48,15 +48,15 @@ social:
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# - icon: twitter
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# icon_pack: fab
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# link: https://twitter.com/GeorgeCushen
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- icon: google-scholar
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icon_pack: ai
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link:
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# - icon: google-scholar
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# icon_pack: ai
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# link:
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- icon: github
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icon_pack: fab
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link: https://github.com/noobing
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- icon: home
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icon_pack: fas
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link: https://your-website
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# - icon: home
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# icon_pack: fas
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# link: https://your-website
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# Link to a PDF of your resume/CV from the About widget.
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# To enable, copy your resume/CV to `static/files/cv.pdf` and uncomment the lines below.
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# - icon: cv
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---
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title: 'Comprehensive Evaluation of LLMs in HPC Code Performance Optimization'
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# Authors
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# If you created a profile for a user (e.g. the default `admin` user), write the username (folder name) here
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# and it will be replaced with their full name and linked to their profile.
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authors:
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- Bowen Cui
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- Tejas Ramesh
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- Oscar Hernandez
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- Keren Zhou
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# Author notes (optional)
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# author_notes:
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# - 'Equal contribution'
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# - 'Equal contribution'
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date: '2025-09-13T05:30:00Z'
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doi: ''
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# Schedule page publish date (NOT publication's date).
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publishDate: '2025-11-03T00:00:00Z'
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# Publication type.
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# Accepts a single type but formatted as a YAML list (for Hugo requirements).
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# Enter a publication type from the CSL standard.
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publication_types: ['paper-conference']
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# Publication name and optional abbreviated publication name.
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publication: In The Proceedings of the Workshop on AI Assisted Software Development for HPC
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publication_short: In *AI4Dev 2025*
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abstract: We empirically assess modern large language models on representative HPC code optimization tasks, detailing accuracy, performance gains, and practical guidance for production integration.
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# Summary. An optional shortened abstract.
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# summary: Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis posuere tellus ac convallis placerat. Proin tincidunt magna sed ex sollicitudin condimentum.
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tags: []
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# Display this page in the Featured widget?
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featured: false
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# Custom links (uncomment lines below)
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# links:
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# - name: Custom Link
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# url: http://example.org
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url_pdf: 'https://arxiv.org/abs/2503.13772'
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# url_code: 'https://github.com/HugoBlox/hugo-blox-builder'
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# url_dataset: 'https://github.com/HugoBlox/hugo-blox-builder'
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# url_poster: ''
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# url_project: ''
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# url_slides: 'uploads/MLSH2024.pdf'
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# url_source: 'https://github.com/HugoBlox/hugo-blox-builder'
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# url_video: 'https://youtube.com'
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# Featured image
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# To use, add an image named `featured.jpg/png` to your page's folder.
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# image:
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# caption: 'Image credit: [**Unsplash**](https://unsplash.com/photos/pLCdAaMFLTE)'
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# focal_point: ''
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# preview_only: false
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# Associated Projects (optional).
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# Associate this publication with one or more of your projects.
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# Simply enter your project's folder or file name without extension.
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# E.g. `internal-project` references `content/project/internal-project/index.md`.
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# Otherwise, set `projects: []`.
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# projects:
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# - example
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# Slides (optional).
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# Associate this publication with Markdown slides.
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# Simply enter your slide deck's filename without extension.
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# E.g. `slides: "example"` references `content/slides/example/index.md`.
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# Otherwise, set `slides: ""`.
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# slides: example
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---
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<!-- {{% callout note %}}
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Click the _Cite_ button above to demo the feature to enable visitors to import publication metadata into their reference management software.
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{{% /callout %}}
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{{% callout note %}}
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Create your slides in Markdown - click the _Slides_ button to check out the example.
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{{% /callout %}} -->
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<!-- Add the publication's **full text** or **supplementary notes** here. You can use rich formatting such as including [code, math, and images](https://docs.hugoblox.com/content/writing-markdown-latex/). -->
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---
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title: 'DeepContext: A Context-aware, Cross-platform, and Cross-framework Tool for Performance Profiling and Analysis of Deep Learning Workloads'
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# Authors
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# If you created a profile for a user (e.g. the default `admin` user), write the username (folder name) here
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# and it will be replaced with their full name and linked to their profile.
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authors:
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- Qidong Zhao
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- Hao Wu
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- Yuming Hao
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- Zilingfeng Ye
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- Jiajia Li
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- Xu Liu
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- Keren Zhou
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# Author notes (optional)
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# author_notes:
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# - 'Equal contribution'
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# - 'Equal contribution'
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date: '2025-04-13T05:30:00Z'
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doi: ''
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# Schedule page publish date (NOT publication's date).
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publishDate: '2025-11-03T00:00:00Z'
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# Publication type.
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# Accepts a single type but formatted as a YAML list (for Hugo requirements).
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# Enter a publication type from the CSL standard.
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publication_types: ['paper-conference']
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# Publication name and optional abbreviated publication name.
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publication: In The Proceedings of the 30th ACM International Conference on Architectural Support for Programming Languages and Operating Systems
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publication_short: In *ASPLOS 2025*
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abstract: DeepContext delivers cross-platform insights into deep learning workloads by combining context-aware profiling with actionable diagnostics for developers and performance engineers.
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# Summary. An optional shortened abstract.
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# summary: Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis posuere tellus ac convallis placerat. Proin tincidunt magna sed ex sollicitudin condimentum.
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tags: []
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# Display this page in the Featured widget?
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featured: false
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# Custom links (uncomment lines below)
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# links:
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# - name: Custom Link
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# url: http://example.org
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url_pdf: 'https://arxiv.org/abs/2411.02797'
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# url_code: 'https://github.com/HugoBlox/hugo-blox-builder'
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# url_dataset: 'https://github.com/HugoBlox/hugo-blox-builder'
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# url_poster: ''
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# url_project: ''
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# url_slides: 'uploads/MLSH2024.pdf'
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# url_source: 'https://github.com/HugoBlox/hugo-blox-builder'
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# url_video: 'https://youtube.com'
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# Featured image
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# To use, add an image named `featured.jpg/png` to your page's folder.
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# image:
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# caption: 'Image credit: [**Unsplash**](https://unsplash.com/photos/pLCdAaMFLTE)'
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# focal_point: ''
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# preview_only: false
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# Associated Projects (optional).
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# Associate this publication with one or more of your projects.
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# Simply enter your project's folder or file name without extension.
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# E.g. `internal-project` references `content/project/internal-project/index.md`.
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# Otherwise, set `projects: []`.
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# projects:
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# - example
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# Slides (optional).
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# Associate this publication with Markdown slides.
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# Simply enter your slide deck's filename without extension.
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# E.g. `slides: "example"` references `content/slides/example/index.md`.
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# Otherwise, set `slides: ""`.
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# slides: example
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---
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<!-- {{% callout note %}}
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Click the _Cite_ button above to demo the feature to enable visitors to import publication metadata into their reference management software.
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{{% /callout %}}
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{{% callout note %}}
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Create your slides in Markdown - click the _Slides_ button to check out the example.
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{{% /callout %}} -->
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<!-- Add the publication's **full text** or **supplementary notes** here. You can use rich formatting such as including [code, math, and images](https://docs.hugoblox.com/content/writing-markdown-latex/). -->
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---
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title: 'Deep Learning-based GPU Simulation for Agile Architecture-Algorithm Co-design'
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# Authors
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# If you created a profile for a user (e.g. the default `admin` user), write the username (folder name) here
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# and it will be replaced with their full name and linked to their profile.
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authors:
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- Junyu Yin
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- Lingda Li
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- Hai Van Duong
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- Keren Zhou
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# Author notes (optional)
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# author_notes:
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# - 'Equal contribution'
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# - 'Equal contribution'
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date: '2024-10-13T05:30:00Z'
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doi: ''
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# Schedule page publish date (NOT publication's date).
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publishDate: '2025-11-03T00:00:00Z'
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# Publication type.
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# Accepts a single type but formatted as a YAML list (for Hugo requirements).
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# Enter a publication type from the CSL standard.
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publication_types: ['paper-conference']
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# Publication name and optional abbreviated publication name.
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publication: In The 4th International Workshop on Machine Learning for Software Hardware Co-Design
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publication_short: In *MLSH 2024*
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# abstract: Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis posuere tellus ac convallis placerat. Proin tincidunt magna sed ex sollicitudin condimentum. Sed ac faucibus dolor, scelerisque sollicitudin nisi. Cras purus urna, suscipit quis sapien eu, pulvinar tempor diam. Quisque risus orci, mollis id ante sit amet, gravida egestas nisl. Sed ac tempus magna. Proin in dui enim. Donec condimentum, sem id dapibus fringilla, tellus enim condimentum arcu, nec volutpat est felis vel metus. Vestibulum sit amet erat at nulla eleifend gravida.
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# Summary. An optional shortened abstract.
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# summary: Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis posuere tellus ac convallis placerat. Proin tincidunt magna sed ex sollicitudin condimentum.
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tags: []
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# Display this page in the Featured widget?
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featured: false
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# Custom links (uncomment lines below)
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# links:
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# - name: Custom Link
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# url: http://example.org
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# url_pdf: 'uploads/MLSH2024.pdf'
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# url_code: 'https://github.com/HugoBlox/hugo-blox-builder'
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# url_dataset: 'https://github.com/HugoBlox/hugo-blox-builder'
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# url_poster: ''
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# url_project: ''
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url_slides: 'uploads/MLSH2024.pdf'
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# url_source: 'https://github.com/HugoBlox/hugo-blox-builder'
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# url_video: 'https://youtube.com'
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# Featured image
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# To use, add an image named `featured.jpg/png` to your page's folder.
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# image:
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# caption: 'Image credit: [**Unsplash**](https://unsplash.com/photos/pLCdAaMFLTE)'
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# focal_point: ''
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# preview_only: false
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# Associated Projects (optional).
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# Associate this publication with one or more of your projects.
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# Simply enter your project's folder or file name without extension.
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# E.g. `internal-project` references `content/project/internal-project/index.md`.
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# Otherwise, set `projects: []`.
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# projects:
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# - example
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# Slides (optional).
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# Associate this publication with Markdown slides.
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# Simply enter your slide deck's filename without extension.
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# E.g. `slides: "example"` references `content/slides/example/index.md`.
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# Otherwise, set `slides: ""`.
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# slides: example
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---
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<!-- {{% callout note %}}
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Click the _Cite_ button above to demo the feature to enable visitors to import publication metadata into their reference management software.
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{{% /callout %}}
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{{% callout note %}}
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Create your slides in Markdown - click the _Slides_ button to check out the example.
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{{% /callout %}} -->
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<!-- Add the publication's **full text** or **supplementary notes** here. You can use rich formatting such as including [code, math, and images](https://docs.hugoblox.com/content/writing-markdown-latex/). -->
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---
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title: 'SS1: Accelerating Inference with Fast and Expressive Sketch Structured Transform'
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# Authors
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# If you created a profile for a user (e.g. the default `admin` user), write the username (folder name) here
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# and it will be replaced with their full name and linked to their profile.
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authors:
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- Kimia Saedi
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- Aditya Desai
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- Apoorv Walia
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- Jihyeong Lee
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- Keren Zhou
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- Anshumali Shrivastava
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# Author notes (optional)
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# author_notes:
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# - 'Equal contribution'
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# - 'Equal contribution'
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date: '2024-12-15T05:30:00Z'
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doi: ''
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# Schedule page publish date (NOT publication's date).
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publishDate: '2025-11-03T00:00:00Z'
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# Publication type.
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# Accepts a single type but formatted as a YAML list (for Hugo requirements).
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# Enter a publication type from the CSL standard.
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publication_types: ['paper-conference']
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# Publication name and optional abbreviated publication name.
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publication: In The Thirty-eighth Annual Conference on Neural Information Processing Systems
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publication_short: In *NeurIPS 2024*
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abstract: Tensor multiplication with learned weight matrices is the fundamental building block in deep learning models. These matrices can often be sparsified, decomposed, quantized, or subjected to random parameter sharing without losing accuracy, suggesting the possibility of more efficient transforms. Although many variants of weight matrices exist, unstructured ones are incompatible with modern hardware, slowing inference and training. On the other hand, structured variants often limit expressivity or fail to deliver the promised latency benefits. We present Sketch Structured Transform (SS1), an expressive and GPU-friendly operator that accelerates inference. SS1 leverages parameter sharing in a random yet structured manner to reduce computation while retraining the rich expressive nature of parameter sharing. We confirm empirically that SS1 offers better quality-efficiency tradeoffs than competing variants. Interestingly SS1 can be combined with Quantization to achieve gains unattainable by either method alone, a finding we justify via theoretical analysis. The analysis may be of independent interest.Moreover, existing pre-trained models can be projected onto SS1 and finetuned for efficient deployment. Surprisingly, these projected models can perform reasonably well even without finetuning. Our experiments highlight various applications of the SS1:(a) Training GPT2 and DLRM models from scratch for faster inference. (b) Finetuning projected BERT models for 1.31× faster inference while maintaining GLUE scores. (c) Proof of concept with Llama-3-8b, showing 1.11× faster wall clock inference using projected SS1 layers without finetuning. We open source our code :https://github.com/apd10/Sketch-Structured-Linear/
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# Summary. An optional shortened abstract.
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# summary: Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis posuere tellus ac convallis placerat. Proin tincidunt magna sed ex sollicitudin condimentum.
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tags: []
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# Display this page in the Featured widget?
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featured: false
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# Custom links (uncomment lines below)
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# links:
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# - name: Custom Link
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# url: http://example.org
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url_pdf: 'https://proceedings.neurips.cc/paper_files/paper/2024/file/57ef0373c890b30407eadfe6e06c8c84-Paper-Conference.pdf'
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# url_code: 'https://github.com/HugoBlox/hugo-blox-builder'
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# url_dataset: 'https://github.com/HugoBlox/hugo-blox-builder'
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# url_poster: ''
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# url_project: ''
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# url_slides: 'uploads/MLSH2024.pdf'
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# url_source: 'https://github.com/HugoBlox/hugo-blox-builder'
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# url_video: 'https://youtube.com'
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# Featured image
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# To use, add an image named `featured.jpg/png` to your page's folder.
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# image:
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# caption: 'Image credit: [**Unsplash**](https://unsplash.com/photos/pLCdAaMFLTE)'
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# focal_point: ''
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# preview_only: false
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# Associated Projects (optional).
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# Associate this publication with one or more of your projects.
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# Simply enter your project's folder or file name without extension.
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# E.g. `internal-project` references `content/project/internal-project/index.md`.
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# Otherwise, set `projects: []`.
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# projects:
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# - example
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# Slides (optional).
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# Associate this publication with Markdown slides.
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# Simply enter your slide deck's filename without extension.
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# E.g. `slides: "example"` references `content/slides/example/index.md`.
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# Otherwise, set `slides: ""`.
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# slides: example
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---
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<!-- {{% callout note %}}
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Click the _Cite_ button above to demo the feature to enable visitors to import publication metadata into their reference management software.
84+
{{% /callout %}}
85+
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{{% callout note %}}
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Create your slides in Markdown - click the _Slides_ button to check out the example.
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{{% /callout %}} -->
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<!-- Add the publication's **full text** or **supplementary notes** here. You can use rich formatting such as including [code, math, and images](https://docs.hugoblox.com/content/writing-markdown-latex/). -->

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