4 citations · 6 across the 4 of their papers we have counts for
5 papers · 1 filter
CONFERM: Recurrence-Aware Temporal Mapping for Multi-Cycle Multi-Context CGRAs
Jun Yin, Jannes Willemen, Stef Cuyckens +2
Throughput in DSP and machine learning workloads is often limited by two temporal structures, i.e., loop-carried recurrences and long-latency, multi-cycle compute nodes. On spatio-…
ARES: Adaptive Reasoning-Effort Steering for PPA- and Cost-Aware RTL Optimization with LLM Agents
Stef Cuyckens, Mihaela Jivanescu, Jun Yin +2
Large language model (LLM) agents optimize the power, performance, and area (PPA) of register-transfer-level (RTL) designs by iterating over edits, synthesis, and PPA analysis, pay…
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…