- Hands-On GPU Programming with Python and CUDA
- Dr. Brian Tuomanen
- 84字
- 2021-06-10 19:25:39
Technical requirements
A Linux or Windows 10 PC with a modern NVIDIA GPU (2016 onward) is required for this chapter, with all necessary GPU drivers and the CUDA Toolkit (9.0 onward) installed. A suitable Python 2.7 installation (such as Anaconda Python 2.7) with the PyCUDA module is also required.
This chapter's code is also available on GitHub at https://github.com/PacktPublishing/Hands-On-GPU-Programming-with-Python-and-CUDA.
For more information about the prerequisites, check the Preface of this book; for the software and hardware requirements, check the README section in https://github.com/PacktPublishing/Hands-On-GPU-Programming-with-Python-and-CUDA.
推薦閱讀
- pcDuino開發(fā)實戰(zhàn)
- Learn Helm
- Mastering KVM Virtualization
- PLC控制系統(tǒng)應(yīng)用與維護
- 循序漸進學(xué)Docker
- 嵌入式Linux驅(qū)動程序和系統(tǒng)開發(fā)實例精講
- Alfresco 4 Enterprise Content Management Implementation
- Instant Optimizing Embedded Systems using Busybox
- 網(wǎng)絡(luò)操作系統(tǒng)管理與應(yīng)用（第三版）
- Windows 7案例教程
- 從實踐中學(xué)習(xí)Kali Linux無線網(wǎng)絡(luò)滲透測試
- Red Hat Enterprise Linux 6.4網(wǎng)絡(luò)操作系統(tǒng)詳解
- Advanced Infrastructure Penetration Testing
- Linux內(nèi)核API完全參考手冊（第2版）
- 大學(xué)計算機應(yīng)用基礎(chǔ)實踐教程（Windows 7+MS Office 2010）