Posts tagged C++

Llama.cpp Meets Instinct: A New Era of Open-Source AI Acceleration

Llama.cpp is an open source implementation of a Large Language Model (LLM) inference framework designed to run efficiently on diverse hardware configurations, both locally and in cloud environments. Its plain C/C++ implementation ensures a dependency-free setup, allowing it to seamlessly support various hardware architectures across CPUs and GPUs. The framework offers a range of quantization options, including 1.5-bit to 8-bit integer quantization, to achieve faster inference and reduced memory usage. Llama.cpp is part of an active open-source community within the AI ecosystem, with over 1200 contributors and almost 4000 releases on its official GitHub repository as of early August, 2025. Designed as a CPU-first C++ library, llama.cpp offers simplicity and easy integration with other programming environments - making it widely compatible and rapidly adopted across diverse platforms, especially among consumer devices.

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ROCm Revisited: Getting Started with HIP

This blog is part of our ROCm Revisited series[1]. The purpose of this series is to share the story of ROCm and our journey through the changes and successes we’ve achieved over the past few years.

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C++17 parallel algorithms and HIPSTDPAR

The C++17 standard added the concept of parallel algorithms to the pre-existing C++ Standard Library. The parallel version of algorithms like std::transform maintain the same signature as the regular serial version, except for the addition of an extra parameter specifying the execution policy to use. This flexibility allows users that are already using the C++ Standard Library algorithms to take advantage of multi-core architectures by just introducing minimal changes to their code.

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PyTorch C++ Extension on AMD GPU

16, Apr 2024 by

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