ROCm Deep Dive (eBook, ePUB)
Definitive Reference for Developers and Engineers
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"ROCm Deep Dive" "ROCm Deep Dive" is a definitive guide for practitioners and researchers seeking a comprehensive understanding of the Radeon Open Compute (ROCm) platform. The book begins by grounding readers in ROCm's historical evolution, architectural underpinnings, and its distinctive approach to heterogeneous computing, contrasting it with prevailing standards such as CUDA and OpenCL. This foundation is expertly extended to cover practical deployment and tuning across diverse AMD hardware, ensuring developers and systems architects can confidently establish robust environments tailored fo...
"ROCm Deep Dive"
"ROCm Deep Dive" is a definitive guide for practitioners and researchers seeking a comprehensive understanding of the Radeon Open Compute (ROCm) platform. The book begins by grounding readers in ROCm's historical evolution, architectural underpinnings, and its distinctive approach to heterogeneous computing, contrasting it with prevailing standards such as CUDA and OpenCL. This foundation is expertly extended to cover practical deployment and tuning across diverse AMD hardware, ensuring developers and systems architects can confidently establish robust environments tailored for high-performance GPU computing.
Delving into the technical heart of ROCm, the book unpacks its innovative execution model, advanced memory hierarchies, and the orchestration of compute kernels. Readers are guided through HIP programming, compiler toolchains, and device-specific optimizations-empowering them to port and optimize complex codebases from CUDA while leveraging ROCm's powerful profiling, debugging, and performance modeling tools. Detailed attention is paid to system integration, from kernel drivers to runtime services, highlighting design strategies for secure, efficient, and scalable multi-GPU systems in both on-premises and cloud-based deployments.
The book culminates by exploring the vibrant ROCm ecosystem and its trajectory. It features in-depth coverage of core libraries, machine learning acceleration, and distributed computation, personalized for both emerging AI workloads and traditional HPC. Comprehensive chapters address operationalizing ROCm at scale-including containerization, CI/CD pipelines, monitoring, and security hardening-while a forward-looking analysis prepares readers for the next wave of innovation in heterogeneous compute standards, community-driven development, and sustainable coding practices. "ROCm Deep Dive" is an indispensable resource for mastering state-of-the-art, open source GPU computing.
"ROCm Deep Dive" is a definitive guide for practitioners and researchers seeking a comprehensive understanding of the Radeon Open Compute (ROCm) platform. The book begins by grounding readers in ROCm's historical evolution, architectural underpinnings, and its distinctive approach to heterogeneous computing, contrasting it with prevailing standards such as CUDA and OpenCL. This foundation is expertly extended to cover practical deployment and tuning across diverse AMD hardware, ensuring developers and systems architects can confidently establish robust environments tailored for high-performance GPU computing.
Delving into the technical heart of ROCm, the book unpacks its innovative execution model, advanced memory hierarchies, and the orchestration of compute kernels. Readers are guided through HIP programming, compiler toolchains, and device-specific optimizations-empowering them to port and optimize complex codebases from CUDA while leveraging ROCm's powerful profiling, debugging, and performance modeling tools. Detailed attention is paid to system integration, from kernel drivers to runtime services, highlighting design strategies for secure, efficient, and scalable multi-GPU systems in both on-premises and cloud-based deployments.
The book culminates by exploring the vibrant ROCm ecosystem and its trajectory. It features in-depth coverage of core libraries, machine learning acceleration, and distributed computation, personalized for both emerging AI workloads and traditional HPC. Comprehensive chapters address operationalizing ROCm at scale-including containerization, CI/CD pipelines, monitoring, and security hardening-while a forward-looking analysis prepares readers for the next wave of innovation in heterogeneous compute standards, community-driven development, and sustainable coding practices. "ROCm Deep Dive" is an indispensable resource for mastering state-of-the-art, open source GPU computing.
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