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Saleh Ashkboos
Research Assistant at Scalable Parallel Computing Lab
Computer Science Department,
ETH Zürich. |
About
I'm a second-year Ph.D. student in the Computer Science Department of ETH Zurich. I am fortunate to be advised by Professor Torsten Hoefler and
Professor Dan Alistarh.
My research focuses on accelerating deep neural network training. Also, I'm working on developing systems and algorithms for large scale graph processing.
Before joining ETH, I received my Master's degree in Computer Science from the Sharif University of Technology advised by Professor Amir Daneshgar in 2019.
News
2023/01: "GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers" accepted at ICLR23.
2022/11: "ProbGraph: High-Performance and High-Accuracy Graph Mining with Probabilistic Set Representations " selected as the best paper at SC22.
2022/09: "ENS-10: A Dataset For Post-Processing Ensemble Weather Forecasts " accepted at Neurips22. (Github)
2022/08: "ProbGraph: High-Performance and High-Accuracy Graph Mining with Probabilistic Set Representations " selected as the best paper finalist at SC22.
2022/08: "ProbGraph: High-Performance and High-Accuracy Graph Mining with Probabilistic Set Representations " accepted at SC22.
2022/07: I will join AxeleraAI for a summer internship.
2022/05: "Motif Prediction with Graph Neural Networks " accepted at KDD'22.
2021/05: "Flare: Flexible In-Network Allreduce " accepted at SC21.
2021/04: I Joined SPCL Lab.
2021/01: "New Bounds For Distributed Mean Estimation and Variance Reduction" accepted at ICLR 2021.
2020/08: "Multi-way sparsest cut problem on trees with a control on the number of parts and outliers" accepted at Discrete Applied Mathematics.
2020/01: I successfully defended my Master dissertation.
2019/10: "Sparcml: High-performance sparse communication for machine learning" accepted at SC19.