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Yuke Wang Profile
Yuke Wang

@YukeWang1

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2K
Following
962
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Statuses
34

Assistant Professor at Rice CS | CS Ph.D. at UCSB | Deep Learning System | ex- Amazon, Microsoft Research, NVIDIA Research | NVIDIA Graduate Fellowship’22.

Houston, TX
Joined July 2019
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@tianyin_xu
Tianyin Xu
11 months
Xudong Sun is on the faculty job market. He is truly brilliant, and has been doing exciting research on System Verification and Software Testing towards the vision of provably correct cloud infra and systems. His materials can be found at, https://t.co/cXdlm4HzTT Interview him;
@xu_dong_sun
Xudong Sun
11 months
@ManlingLi_ Thank you for sharing, Manling! I am on the job market and this is very helpful!
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@YukeWang1
Yuke Wang
1 year
I will be hiring 2~3 PhD students at Rice CS in the Fall of 2025 in the system for deep learning. Feel free to reach out and apply by Jan.1, 2025. No application fee!
csweb.rice.edu
Graduate Program Application Thank you for your interest in computer science graduate studies at Rice University.
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@YukeWang1
Yuke Wang
1 year
Rice CS/ECE is hiring for tenure-track faculty position in Computer System. Feel free to check out this post for more detail.
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@anjiangw
Anjiang Wei
1 year
🤝 New work on LLM for code optimization with @allen_a_nie, @brohanster, and amazing teams at Stanford, Intel, NVIDIA, and Visa Research. We show how LLMs can generate system code that outperforms human experts in parallel matrix multiplication. 🧠🔧 🔗 https://t.co/n3S1FREtIn
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@YukeWang1
Yuke Wang
2 years
The USENIX ATC and OSDI '24 Artifact Evaluation Committee are looking for members of the Artifact Evaluation Committee (AEC), who will contribute to the OSDI and ATC Artifact Evaluation. Sunday 28th April, Anywhere on Earth https://t.co/Mj7XMni03H
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docs.google.com
We are looking for members of the Artifact Evaluation Committee (AEC), who will contribute to the OSDI and ATC Artifact Evaluation (AE) process by reviewing submitted artifacts. AEC membership is...
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@StudentsSystems
Students @ Systems
2 years
📢 Fellowships as a Grad Student! We are back with an exciting panel to help you with graduate fellowship applications! With Shimaa Ahmed, @YukeWang1 , Mark Zhao, @yangzhouy 📆 Apr 26 Register for free and submit questions: https://t.co/vYY5yYCvZj
@StudentsSystems
Students @ Systems
2 years
📢Panel on Fellowships as a Grad Student With April around, we are looking to organize a panel on getting fellowships as a grad student. Vote the topics you'd like to see the most. Ask questions and read more at
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@RobinDing3
Yangruibo Robin Ding
2 years
🚨Is your Code LM good enough at understanding the cross-file context when completing the program? Come and challenge it!! We will present a diverse and multilingual benchmark, CrossCodeEval, at @NeurIPSConf 2023! See you in New Orleans!
@zijianwang30
Zijian Wang
2 years
🚀Introducing #CrossCodeEval, a diverse and multilingual code completion benchmark that necessitates cross-file contextual understanding for accurate code completion. To appear at #NeurIPS2023 D&B Track, co-led w/ @RobinDing3 @ahmadwasi https://t.co/Z8xY5O18ay 🧵1/9
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@YukeWang1
Yuke Wang
2 years
Hi, Everyone, I will be on the academic job market for 2024 Fall, with a research focus on Systems for Deep Learning and GPU-based Parallel and Distributed Programming. Feel free to reach out if your department has open positions. Thanks!
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@YukeWang1
Yuke Wang
2 years
I will present our USENIX OSDI'23 paper Tomorrow (July 12) at 11:15am in Grand Ballroom Complex at Sheraton Hotel Boston. [Paper] https://t.co/BNJrmTfyJ3 [Code] https://t.co/k4pOuLQYGZ Feel free to come by~
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github.com
Artifact for OSDI'23: MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Multi-GPU Platforms. - YukeWang96/MGG_OSDI23
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@YukeWang1
Yuke Wang
2 years
I will present our USENIX ATC‘23 paper Tomorrow (July 10) at 1:40 pm in Constitution Ballroom B at Sheraton Hotel Boston. TC-GNN: Bridging Sparse GNN Computation and Dense Tensor Cores on GPUs [Paper] https://t.co/ap6G7jNBBk [Code] https://t.co/YEUYFGZOod Feel free to come by~
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github.com
Artifact for USENIX ATC'23: TC-GNN: Bridging Sparse GNN Computation and Dense Tensor Cores on GPUs. - YukeWang96/TC-GNN_ATC23
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@YukeWang1
Yuke Wang
3 years
I am glad to share that our paper “TC-GNN: Bridging Sparse GNN Computation and Dense Tensor Cores on GPUs” has been accepted to USENIX ATC’23. This year we have 1 x OSDI and 1 x ATC paper in the co-located two conferences in Boston. Thanks to all collaborators!
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@YukeWang1
Yuke Wang
3 years
I am glad to share that our paper “Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Multi-GPU Platforms” has been accepted to OSDI’23, Thanks to all collaborators! See you in Boston in summer!
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@YukeWang1
Yuke Wang
4 years
+ S41082 APNN-TC: Accelerating Arbitrary Precision Neural Networks on Ampere GPU Tensor Cores. [GTC session link] https://t.co/8uifZ5Nrpg [paper] https://t.co/7wb8sPePOg [slides] https://t.co/BAO5ZFSlf1 [code]
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@YukeWang1
Yuke Wang
4 years
+ S41234 Accelerating Sparse Graph Neural Network Computation via Dense Tensor Core on GPUs. [GTC session link] https://t.co/ckPpAGqWpe [paper] https://t.co/ouRmaGS5ft [slides] https://t.co/Va66dccpsk [code]
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@YukeWang1
Yuke Wang
4 years
Feel free to mark and save two technical sessions from our group at @NVIDIAGTC. And I will lead the first one (S41234). We have our paper, slides, and code publicly available for access. Check more details in this thread.
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@YukeWang1
Yuke Wang
4 years
Feel free to check out our PPoPP'22 paper on Quantized Graph Neural Network Acceleration on GPU Tensor Cores Paper: https://t.co/M51TUd5Nor Code:
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github.com
Artifact for PPoPP22 QGTC: Accelerating Quantized GNN via GPU Tensor Core. - YukeWang96/QGTC_PPoPP22
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@YukeWang1
Yuke Wang
4 years
Very Glad 😀 to be elected as an recipient of NVIDIA Graduate fellowship this year~ NVIDIA Awards $50,000 Fellowships to Ph.D. Students for GPU Computing Research
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blogs.nvidia.com
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@YukeWang1
Yuke Wang
4 years
I will be presenting our paper "An Efficient Quantitative Approach for Optimizing Convolutional Neural Networks" ( https://t.co/d9JF14oUJy) @CIKM2021 at the session "3E: Scalability issues in Machine Learning" PDT 17:40 - 18:50 Nov.2 and PDT 5:40 - 6:50 Nov.3, Welcome to join!😀
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dl.acm.org
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