ROCm: Open Compute for AMD GPUs (eBook, ePUB)
The Complete Guide for Developers and Engineers
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"ROCm: Open Compute for AMD GPUs" "ROCm: Open Compute for AMD GPUs" is an authoritative guide to the rapidly evolving world of open, high-performance GPU computing on AMD hardware. This book provides a thorough exploration of the ROCm platform, beginning with its motivations and architectural foundations, and contrasting its open, vendor-neutral approach against proprietary solutions. Readers are guided through the nuanced landscape of accelerator programming-from the underlying hardware architecture and software stack to in-depth discussions of usability, interoperability with existing framew...
"ROCm: Open Compute for AMD GPUs"
"ROCm: Open Compute for AMD GPUs" is an authoritative guide to the rapidly evolving world of open, high-performance GPU computing on AMD hardware. This book provides a thorough exploration of the ROCm platform, beginning with its motivations and architectural foundations, and contrasting its open, vendor-neutral approach against proprietary solutions. Readers are guided through the nuanced landscape of accelerator programming-from the underlying hardware architecture and software stack to in-depth discussions of usability, interoperability with existing frameworks, and deployment across a range of hardware and cluster environments.
Delving deeply into the HIP programming model, the text offers detailed explanations of core language constructs, optimizations for AMD GPUs, and strategies for porting and developing robust, high-performance applications. The book further illuminates ROCm's powerful ecosystem of libraries-such as rocBLAS, MIOpen, and rocFFT-demonstrating their application in AI, machine learning, scientific computing, and specialized analytic workloads. Practical sections on system installation, containerized deployment, and Kubernetes orchestration equip engineers and researchers with the skills needed to build, scale, and maintain ROCm-driven compute clusters in production and research settings.
Crucially, the book also addresses advanced topics such as performance engineering, security, reliability, and compliance, ensuring that readers can deliver efficient, secure GPU solutions. Real-world case studies and profiling guidance empower practitioners to diagnose bottlenecks, enhance energy efficiency, and guarantee system integrity. The concluding chapters foster active engagement with the ROCm open-source community, outlining pathways for contribution, extension, and future research directions in open GPU compute. This text is an essential resource for developers, engineers, and decision-makers dedicated to pushing the boundaries of accelerated computing with AMD technologies.
"ROCm: Open Compute for AMD GPUs" is an authoritative guide to the rapidly evolving world of open, high-performance GPU computing on AMD hardware. This book provides a thorough exploration of the ROCm platform, beginning with its motivations and architectural foundations, and contrasting its open, vendor-neutral approach against proprietary solutions. Readers are guided through the nuanced landscape of accelerator programming-from the underlying hardware architecture and software stack to in-depth discussions of usability, interoperability with existing frameworks, and deployment across a range of hardware and cluster environments.
Delving deeply into the HIP programming model, the text offers detailed explanations of core language constructs, optimizations for AMD GPUs, and strategies for porting and developing robust, high-performance applications. The book further illuminates ROCm's powerful ecosystem of libraries-such as rocBLAS, MIOpen, and rocFFT-demonstrating their application in AI, machine learning, scientific computing, and specialized analytic workloads. Practical sections on system installation, containerized deployment, and Kubernetes orchestration equip engineers and researchers with the skills needed to build, scale, and maintain ROCm-driven compute clusters in production and research settings.
Crucially, the book also addresses advanced topics such as performance engineering, security, reliability, and compliance, ensuring that readers can deliver efficient, secure GPU solutions. Real-world case studies and profiling guidance empower practitioners to diagnose bottlenecks, enhance energy efficiency, and guarantee system integrity. The concluding chapters foster active engagement with the ROCm open-source community, outlining pathways for contribution, extension, and future research directions in open GPU compute. This text is an essential resource for developers, engineers, and decision-makers dedicated to pushing the boundaries of accelerated computing with AMD technologies.
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