7 citations · 17 across the 21 of their papers we have counts for
5 papers · 1 filter
Attamba: Attending To Multi-Token States
Yash Akhauri, Safeen Huda, Mohamed S. Abdelfattah
When predicting the next token in a sequence, vanilla transformers compute attention over all previous tokens, resulting in quadratic scaling of compute with sequence length. State…
ShadowLLM: Predictor-based Contextual Sparsity for Large Language Models
Yash Akhauri, Ahmed F AbouElhamayed, Jordan Dotzel +4
The high power consumption and latency-sensitive deployments of large language models (LLMs) have motivated efficiency techniques like quantization and sparsity. Contextual sparsit…
Radial Networks: Dynamic Layer Routing for High-Performance Large Language Models
Jordan Dotzel, Yash Akhauri, Ahmed S. AbouElhamayed +3
Large language models (LLMs) often struggle with strict memory, latency, and power demands. To meet these demands, various forms of dynamic sparsity have been proposed that reduce…
Encodings for Prediction-based Neural Architecture Search
Yash Akhauri, Mohamed S. Abdelfattah
Predictor-based methods have substantially enhanced Neural Architecture Search (NAS) optimization. The efficacy of these predictors is largely influenced by the method of encoding…
On Latency Predictors for Neural Architecture Search
Yash Akhauri, Mohamed S. Abdelfattah
Efficient deployment of neural networks (NN) requires the co-optimization of accuracy and latency. For example, hardware-aware neural architecture search has been used to automatic…