Large language models often require tens of gigabytes of GPU memory at full precision, making them expensive or impossible to deploy on consumer hardware. This workflow provides three approaches to ...

This workflow automates the process of converting a standard float32 neural network model (in ncnn format) into an int8 quantized model. Quantization replaces 32-bit floating-point weights and ...

Abstract: Quantization is a critical technique employed across various research fields for compressing deep neural networks (DNNs) to facilitate deployment within resource-limited environments. This ...

Abstract: Deep Neural Networks (DNNs) have gained considerable attention in the past decades due to their astounding performance in different applications, such as natural language modeling, ...

引言：跨越三十年的独显远征在半导体发展的长河中，英特尔对独立显卡的执念可以追溯到上世纪 90 年代。从最初本打算切入 RISC 市场的 i860 但是最终作为图形工作站加速器，从 1998 年昙花一现的 i740，再到后来试图通过多核心通用架构重塑图形领域的 Larrabee 项目，英特尔经历了无数次的探索与蛰伏。直到 2018 年，代号 Arctic Sound 的现代独立 GPU 计划正式启动 ...