Computer Architecture: A Quantitative Approach, John L. Hennessy, David A. Patterson, 2017 (Morgan Kaufmann) - Provides a comprehensive foundation on CPU and memory architectures, including cache hierarchies and control logic, essential for understanding the CPU side of the comparison.
Programming Massively Parallel Processors: A Hands-on Approach, Wen-mei W. Hwu, David B. Kirk, Izzat El Hajj, 2022 (Morgan Kaufmann) - Explains GPU architecture, the SIMT model, and the principles of parallel computing, directly relevant to the GPU description and its strengths in parallel processing.
Deep Learning, Ian Goodfellow, Yoshua Bengio, Aaron Courville, 2016 (MIT Press) - Discusses the computational demands of deep learning, particularly large matrix operations, which elucidates why GPUs are uniquely suited for these tasks.
NVIDIA CUDA C++ Programming Guide, NVIDIA Corporation, 2023 (NVIDIA Corporation) - Provides a detailed overview of the CUDA programming model and the underlying GPU architecture, including core concepts like streaming multiprocessors and memory hierarchy.