1 citations · 1 across the 4 of their papers we have counts for
4 papers
SparAMX: Accelerating Compressed LLMs Token Generation on AMX-powered CPUs
Ahmed F. AbouElhamayed, Jordan Dotzel, Yash Akhauri +6
Large language models have high compute, latency, and memory requirements. While specialized accelerators such as GPUs and TPUs typically run these workloads, CPUs are more widely…
Low-Rank Adapters Meet Neural Architecture Search for LLM Compression
J. Pablo Muñoz, Jinjie Yuan, Nilesh Jain
The rapid expansion of Large Language Models (LLMs) has posed significant challenges regarding the computational resources required for fine-tuning and deployment. Recent advanceme…
MultiPruner: Balanced Structure Removal in Foundation Models
J. Pablo Muñoz, Jinjie Yuan, Nilesh Jain
Recently, state-of-the-art approaches for pruning large pre-trained models (LPMs) have demonstrated that the training-free removal of non-critical residual blocks in Transformers i…
SQFT: Low-cost Model Adaptation in Low-precision Sparse Foundation Models
Juan Pablo Muñoz, Jinjie Yuan, Nilesh Jain
Large pre-trained models (LPMs), such as large language models, have become ubiquitous and are employed in many applications. These models are often adapted to a desired domain or…