High Performance Networking

突破效能瓶頸，掌握多核心、GPU加速與大規模資料處理技巧。 實務方法×業界案例，帶你用Python打造生產級效能。 跨越記憶體限制、善用GPU，GenAI與生產化ML的最佳效能解方。 「Ian與Micha的新書不僅介紹現代效能工具，也深入探討程式優化的普遍原則。每一位Python開發者都應該閱讀此書！」 ― Mikhail Timonin，量化開發者，Engelhart 不論你是要處理龐大資料、打造AI產品，還是單純想讓程式更流暢，新版都提供了比前版更強化的工具與方法，讓你的Python程式真正跑出高效能。 收錄GenAI、機器學習產品化等實戰案例，讓你的Python程式在真實環境中全面升級。 ---------------------------------------------------- 或許你的Python程式已經能正確運行，但若能跑得更快，會為你帶來什麼改變？全新第三版《高效能Python程式設計》將引導你找出程式在高資料量環境下的效能瓶頸，並透過各種設計方法與背後的理論基礎，幫助你更深入理解Python的運作，進而寫出真正高效的程式碼。 本書不只涵蓋多核心、叢集與編譯的技巧，也帶你探索如何突破RAM限制、活用GPU加速，甚至在 GenAI、機器學習產品化等場景中提升效能。你將看到許多來自業界的實戰案例，這些公司如何善用高效能Python進行社群分析、AI應用到生產級系統。作者Micha Gorelick與Ian Ozsvald更分享了多年經驗與實用方法，幫助資深Python開發者在不犧牲可靠性的前提下，靈活擴展或縮小系統，迎戰真實世界的效能挑戰。 • 更深入掌握NumPy、Cython與效能分析器。 • 瞭解Python如何將底層電腦架構抽象化。 • 進行效能分析來找出CPU時間與記憶體的使用瓶頸。 • 利用合適的資料結構來寫出高效的程式。 • 提升矩陣與向量運算的速度。 • 使用Pandas、Dask與Polars來快速處理DataFrame。 • 加快神經網路與GPU的計算速度。 • 使用工具來將Python編譯為機器碼。 • 同時管理多個I/O與計算操作。 • 轉換multiprocessing程式碼，並在本地或遠端叢集上運行。

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This book constitutes the refereed proceedings of the First HPCLATAM - CLCAR Joint Latin American High Performance Computing Conference, CARLA 2014, held in Valparaiso, Chile, in October 2014. The 17

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This volume contains 18 contributions to the Third Russian-German Advanced Research Workshop on Computational Science and High Performance Computing presented in July 2007 at Novosibirsk, Russia. The