From the 1 of 5 linked papers with an AI index.
5 papers
ARES: Adaptive Reasoning-Effort Steering for PPA- and Cost-Aware RTL Optimization with LLM Agents
Stef Cuyckens, Mihaela Jivanescu, Jun Yin +2
The paper presents ARES, a framework that adaptively controls the reasoning effort of large language model agents when optimizing RTL designs for power, performance, and area, whil…
MONET: Modeling and Optimization of neural NEtwork Training from Edge to Data Centers
Jérémy Morlier, Robin Geens, Stef Cuyckens +4
While hardware-software co-design has significantly improved the efficiency of neural network inference, modeling the training phase remains a critical yet underexplored challenge.…
Precision-Scalable Microscaling Datapaths with Optimized Reduction Tree for Efficient NPU Integration
Stef Cuyckens, Xiaoling Yi, Robin Geens +4
Emerging continual learning applications necessitate next-generation neural processing unit (NPU) platforms to support both training and inference operations. The promising Microsc…
iEEG Seizure Detection with a Sparse Hyperdimensional Computing Accelerator
Stef Cuyckens, Ryan Antonio, Chao Fang +1
Implantable devices for reliable intracranial electroencephalography (iEEG) require efficient, accurate, and real-time detection of seizures. Dense hyperdimensional computing (HDC)…
Efficient Precision-Scalable Hardware for Microscaling (MX) Processing in Robotics Learning
Stef Cuyckens, Xiaoling Yi, Nitish Satya Murthy +2
Autonomous robots require efficient on-device learning to adapt to new environments without cloud dependency. For this edge training, Microscaling (MX) data types offer a promising…