1 citations · 1 across the 11 of their papers we have counts for
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EfQAT: An Efficient Framework for Quantization-Aware Training
Saleh Ashkboos, Bram Verhoef, Torsten Hoefler +2
Quantization-aware training (QAT) schemes have been shown to achieve near-full precision accuracy. They accomplish this by training a quantized model for multiple epochs. This is c…
MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models
Elias Frantar, Roberto L. Castro, Jiale Chen +2
As inference on Large Language Models (LLMs) emerges as an important workload in machine learning applications, weight quantization has become a standard technique for efficient GP…
SpComm3D: A Framework for Enabling Sparse Communication in 3D Sparse Kernels
Nabil Abubaker, Torsten Hoefler
Existing 3D algorithms for distributed-memory sparse kernels suffer from limited scalability due to reliance on bulk sparsity-agnostic communication. While easier to use, sparsity-…