5 citations · 9 across the 8 of their papers we have counts for
8 papers
A Compute and Communication Runtime Model for Loihi 2
Jonathan Timcheck, Alessandro Pierro, Sumit Bam Shrestha
Neuromorphic computers hold the potential to vastly improve the speed and efficiency of a wide range of computational kernels with their asynchronous, compute-memory co-located, sp…
Evolutionary Mapping of Neural Networks to Spatial Accelerators
Alessandro Pierro, Jonathan Timcheck, Jason Yik +3
Spatial accelerators, composed of arrays of compute-memory integrated units, offer an attractive platform for deploying inference workloads with low latency and low energy consumpt…
Modeling and Optimizing Performance Bottlenecks for Neuromorphic Accelerators
Jason Yik, Walter Gallego Gomez, Andrew Cheng +8
Neuromorphic accelerators offer promising platforms for machine learning (ML) inference by leveraging event-driven, spatially-expanded architectures that naturally exploit unstruct…
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Alessandro Pierro, Steven Abreu, Jonathan Timcheck +3
Linear recurrent neural networks enable powerful long-range sequence modeling with constant memory usage and time-per-token during inference. These architectures hold promise for s…
Solving QUBO on the Loihi 2 Neuromorphic Processor
Alessandro Pierro, Philipp Stratmann, Gabriel Andres Fonseca Guerra +4
In this article, we describe an algorithm for solving Quadratic Unconstrained Binary Optimization problems on the Intel Loihi 2 neuromorphic processor. The solver is based on a har…
Mamba-PTQ: Outlier Channels in Recurrent Large Language Models
Alessandro Pierro, Steven Abreu
Modern recurrent layers are emerging as a promising path toward edge deployment of foundation models, especially in the context of large language models (LLMs). Compressing the who…
Q-S5: Towards Quantized State Space Models
Steven Abreu, Jens E. Pedersen, Kade M. Heckel +1
In the quest for next-generation sequence modeling architectures, State Space Models (SSMs) have emerged as a potent alternative to transformers, particularly for their computation…
Optimization of a Hydrodynamic Computational Reservoir through Evolution
Alessandro Pierro, Kristine Heiney, Shamit Shrivastava +2
As demand for computational resources reaches unprecedented levels, research is expanding into the use of complex material substrates for computing. In this study, we interface wit…