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21 lines
1.4 KiB
Markdown
21 lines
1.4 KiB
Markdown
# Before You Start
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This tutorial introduces how to use the MSCCL++ Primitive API to write highly flexible and optimized GPU communication kernels from the lowest level. If you are looking for the high-level APIs, please refer to the [DSL API](../guide/mscclpp-dsl.md) or the [NCCL API](../quickstart.md#nccl-benchmark).
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## Hardware Requirements
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To run example code in this tutorial, you may need a system with at least two NVIDIA or AMD GPUs. For multi-node examples, you will need RDMA Network Interface Cards (NICs) and a network setup that allows communication between nodes. See the {ref}`prerequisites` for details.
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## Environment Setup
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We provide {ref}`docker-images` and a {ref}`vscode-dev-container` to simplify the environment setup.
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## Prior Knowledge
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This tutorial assumes that readers have a basic understanding of C++ and GPU programming (CUDA). If you are unfamiliar with the following concepts, we recommend reviewing the relevant documentation or tutorials:
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- **C++ Basics:** STL containers, smart pointers, templates, futures, etc.
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- **CUDA Basics:** thread blocks, warps, shared memory, etc.
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- **(Optional) RDMA Basics:** If you are interested in multi-node communication, understanding RDMA concepts (`ibverbs` library) will be helpful.
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In the next page, we will introduce a few basic concepts of the MSCCL++ Primitive API by a simple ping-pong example between two GPUs.
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