Introduction to PTX Programming: With Full Parallel Thread Execution Assembly Code Samples (Mastering Machine Learning)
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Fuera de stock
Fuera de stock
Peso con empaque:
0.33 kg
0.33 kg
Devolución:
No
No
Condición
Nuevo
Nuevo
Producto de:
Amazon
Amazon
Sobre este producto
- Comprehensive, hands-on tutorials spanning 44 meticulously crafted chapters, from foundational vector operations to cutting-edge machine learning, cryptography, and beyond.
- Full PTX assembly code samples that reveal the inner workings of GPU parallelism, empowering you to optimize matrix multiplications, graph traversals, neural networks, and more.
- Real-world applications across industries: accelerate AI model training, simulate astrophysical phenomena, process medical imaging data, optimize financial models, and render photorealistic graphics—all with industry-grade techniques.
- Proven strategies for mastering memory coalescing, thread synchronization, atomic operations, and algorithm design tailored to GPU architectures.
- Learn by doing: Every concept is paired with battle-tested assembly examples, ensuring you grasp both theory and implementation.
- Future-proof your skills: From sparse matrix computations to wavelet transforms and Monte Carlo simulations, tackle tomorrow’s challenges with confidence.
- Bridge the gap between theory and practice: Whether you’re a student, hobbyist, or seasoned professional, the clear explanations and progressive complexity make this the ultimate PTX resource.
- GPU programmers seeking to transcend CUDA abstractions and wield PTX directly.
- Data scientists needing to accelerate clustering, classification, or deep learning workflows.
- Game developers optimizing rendering pipelines or physics engines.
- Researchers in computational biology, quantum simulation, or big data analytics.
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