4 citations · 8 across the 5 of their papers we have counts for
5 papers
Efficient Reasoning on the Edge
Yelysei Bondarenko, Thomas Hehn, Rob Hesselink +15
Large language models (LLMs) with chain-of-thought reasoning achieve state-of-the-art performance across complex problem-solving tasks, but their verbose reasoning traces and large…
Mixture of Cache-Conditional Experts for Efficient Mobile Device Inference
Andrii Skliar, Ties van Rozendaal, Romain Lepert +5
Mixture of Experts (MoE) LLMs have recently gained attention for their ability to enhance performance by selectively engaging specialized subnetworks or "experts" for each input. H…
NeuroSteiner: A Graph Transformer for Wirelength Estimation
Sahil Manchanda, Dana Kianfar, Markus Peschl +2
A core objective of physical design is to minimize wirelength (WL) when placing chip components on a canvas. Computing the minimal WL of a placement requires finding rectilinear St…
Bayesian Optimization for Macro Placement
Changyong Oh, Roberto Bondesan, Dana Kianfar +6
Macro placement is the problem of placing memory blocks on a chip canvas. It can be formulated as a combinatorial optimization problem over sequence pairs, a representation which d…
Simulating Execution Time of Tensor Programs using Graph Neural Networks
Jakub M. Tomczak, Romain Lepert, Auke Wiggers
Optimizing the execution time of tensor program, e.g., a convolution, involves finding its optimal configuration. Searching the configuration space exhaustively is typically infeas…