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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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The paper from Bengisu Elis, Olga Pearce, David Boehme, Jason Burmark, and Martin Schulz won the best paper award. It is accessible on the ACM Digital…

The poster is a work by Kun Qin and Carsten Trinitis presented at the 19th International School on the Effects of Radiation on Embedded Systems for…

Authors: Mohak Chadha, Pulkit Khera, Jianfeng Gu, Osama Abboud (Huawei MRC), and Michael Gerndt Abstract: Federated Learning (FL) is an emerging…

The paper "Systematic Analysis of DDS Implementations", a result of a TUM collaboration with Siemens, was accepted at the Middleware 2023 conference.

Authors: Xiaorang Guo, Kun Qin and Martin Schulz

Aktuelles

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 "Non-Blocking GPU-CPU Notifications to Enable More GPU-CPU Parallelism" won Best Paper Award at HPCAsia24

A compact high-precision FPGA-based Time-to-digital Converter" won the Best Poster Award at SERESSA 2023

Paper titled "Training Heterogeneous Client Models using Knowledge Distillation in Serverless FL” got accepted at the 39th ACM/SIGAPP SAC’24

Accepted Paper at Middleware 2023: "Systematic Analysis of DDS Implementations"

"HiSEP-Q: A Highly Scalable and Efficient Quantum Control Processor for Superconducting Qubits" got accepted at IEEE ICCD 2023