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Authors: Mohak Chadha, Alexander Jensen, Jianfeng Gu, Osama Abboud (Huawei MRC), and Michael Gerndt Abstract: Federated Learning (FL) is an emerging machine learning paradigm that enables the collaborative training of a shared global model across distributed clients while keeping the data…

The paper from David Hildenbrand, Martin Schulz and Nadav Amit won a distinguished artifact award. It is freely accessible on the ACM Digital Library for one month. Link. https://asplos-conference.org/

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Authors: Jonas Winklmann, Martin Schulz and Dimitrios Tsevas

The paper titled "Hierarchical Resource Partitioning on Modern GPUs: A Reinforcement Learning Approach" got accepted at IEEE Cluster 2023

Paper titled "FaST-GShare: Enabling Efficient Spatio-Temporal GPU Sharing in Serverless Computing for DL Inference" got accepted at ACM ICPP 2023.

The paper "DDS Implementations as Real-Time Middleware – A Systematic Evaluation", a result of a TUM collaboration with Siemens, was accepted at the…

The Heidelberg Laureate Forum (HLF) is a networking conference where 200 carefully selected young researchers in mathematics and computer science…

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Paper titled “Apodotiko: Enabling Efficient Serverless Federated Learning in Heterogeneous Environments" got accepted at IEEE/ACM CCGrid’24.

Paper titled “Copy-on-Pin: The Missing Piece for Correct Copy-on-Write" won a Distinguished Artifact Award at ASPLOS'23

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Paper titled "Realistic Neutral Atom Image Simulation" got accepted at IEEE Quantum Week 2023

Paper tiltled "Hierarchical Resource Partitioning on Modern GPUs: A Reinforcement Learning Approach" got accepted at IEEE Cluster 2023

Paper "FaST-GShare: Enabling Efficient Spatio-Temporal GPU Sharing in Serverless Computing for DL Inference" got accepted at ACM ICPP'2023

Accepted Paper at RTCSA23: "DDS Implementations as Real-Time Middleware – A Systematic Evaluation"

Mohak Chadha got selected as a young researcher to participate in the prestigious Heidelberg Laureate Forum (HLF) 2023