157 citations · 166 across the 10 of their papers we have counts for
4 papers · 1 filter
Model Parallelism on Distributed Infrastructure: A Literature Review from Theory to LLM Case-Studies
Felix Brakel, Uraz Odyurt, Ana-Lucia Varbanescu
Neural networks have become a cornerstone of machine learning. As the trend for these to get more and more complex continues, so does the underlying hardware and software infrastru…
Lessons Learned Migrating CUDA to SYCL: A HEP Case Study with ROOT RDataFrame
Jolly Chen, Monica Dessole, Ana Lucia Varbanescu
The world's largest particle accelerator, located at CERN, produces petabytes of data that need to be analysed efficiently, to study the fundamental structures of our universe. ROO…
The Future is Big Graphs! A Community View on Graph Processing Systems
Sherif Sakr, Angela Bonifati, Hannes Voigt +38
Graphs are by nature unifying abstractions that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users a…
Using Graph Properties to Speed-up GPU-based Graph Traversal: A Model-driven Approach
Merijn Verstraaten, Ana Lucia Varbanescu, Cees de Laat
While it is well-known and acknowledged that the performance of graph algorithms is heavily dependent on the input data, there has been surprisingly little research to quantify and…