Jun 16, 2024 · In this paper, we present Tender, an algorithm-hardware co-design solution that enables efficient deployment of LLM inference at low precision.
In this paper, we present Tender, an algorithm-hardware co-design solution that enables efficient deployment of LLM inference at low precision.
Jun 16, 2024 · In this paper, we present Tender, an algorithm-hardware co-design solution that enables efficient deployment of LLM inference at low precision.
Tender: Accelerating Large Language Models via Tensor ... - GitHub
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In this paper, we present Tender, an algorithm-hardware co-design solution that enables efficient deployment of LLM inference at low precision.
Tender. Accelerating Large Language. Models via Tensor Decomposition. And Runtime Requantization. Jungi Lee ([email protected]). Thank You! ISCA-51 | July ...
Jun 20, 2024 · The "Tender" paper introduces two innovative techniques, tensor decomposition and runtime requantization, to significantly accelerate the inference of large ...
Tender: Accelerating Large Language Models via Tensor Decomposition and Runtime Requantization. Jungi Lee*, Wonbeom Lee*, Jaewoong Sim. ISCA, June 2024. [paper] ...
Jun 28, 2024 · Tender: Accelerating Large Language Models via Tensor Decomposition and Runtime Requantization · no code implementations • 16 Jun 2024 • Jungi ...
Tender: Accelerating Large Language Models via Tensor Decomposition and Runtime Requantization · GitHub Repo stars, ISCA, 2024. Unified Low-rank Compression ...
Tender: Accelerating Large Language Models via Tensor Decomposition and Runtime Requantization. no code yet • 16 Jun 2024. Large language models (LLMs) ...