Graphcore Poplar Programming and Optimization: The Complete Guide for Developers and Engineers

"Graphcore Poplar Programming and Optimization"

Unlock the full power of Graphcore’s Intelligence Processing Unit (IPU) ecosystem with "Graphcore Poplar Programming and Optimization," the definitive guide for engineers, data scientists, and researchers seeking to harness state-of-the-art hardware for AI and high-performance computing. This book opens with a deep dive into IPU architecture, elucidating the foundational hardware principles, memory hierarchies, and novel tile-based parallelism that distinguish IPUs from traditional CPUs and GPUs. Readers will gain a robust understanding of the communication pathways, supported data types, and the challenges of scaling solutions across complex, multi-IPU systems—critical knowledge for deploying performant applications on this cutting-edge platform.

Building on these fundamentals, the book meticulously walks through the Poplar SDK—from core programming models and tensor manipulation to constructing optimized data and compute graphs. It covers advanced topics such as memory management, operation fusion, performance tuning, and debugging within the Poplar environment, all supported by detailed case studies showing real-world, complex workflow optimizations. Special attention is given to integration with popular machine learning frameworks like PyTorch and TensorFlow, seamless interoperability with distributed and automated deployment pipelines, and the essential DevOps methodologies for scalable, reproducible model acceleration.

To bring it all together, "Graphcore Poplar Programming and Optimization" explores pioneering research directions, profiling and analysis mastery with the PopVision Suite, and practical strategies for scaling across distributed IPU clusters while maintaining computational integrity and security. With comprehensive coverage of automation, performance benchmarking, and community-driven standards, this book equips practitioners at every level to drive innovation in AI, scientific computing, and beyond—heralding the next era of programmable accelerators.

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전자책: 2025년 7월 24일