The Heterogeneous Interface for Portability (HIP) is AMD’s dedicated GPU programming environment for designing high performance kernels on GPU hardware. HIP is a C++ runtime API and programming language that allows developers to create portable applications on different platforms. This means that developers can write their GPU applications and with very minimal changes be able to run their code in any environment. This module provides in-depth training on programming with HIP.
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➤ Deep Dive into GPU and Performance Optimizations
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➤ Your First HIP Code: Vector Add
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➤ HIP using ROCm Profiler: Matrix Transpose
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➤ Matrix Transpose Part 2: Naïve Version
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➤ Matrix Transpose Part 3: Optimized LDS Version
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➤ Matrix Transpose Part 4: Key Takeaways
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➤ Debugging Tips and Tricks
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➤ Debugging Tips and Tricks: Wrap-up
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CUDA to HIP
HIP code can run on multiple platforms and provides the much-needed code portability in today’s world.HIP also allows for easy porting of code from CUDA, allowing developers to run CUDA applications on ROCm with ease. This module will walk through the porting process in detail through examples.
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➤ Converting a simple application
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➤ Porting Deep Learning CUDA-CNN to HIP
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➤ Porting Machine Learning K-means to HIP
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➤ Wrap-up: Porting from CUDA to HIP
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