学习 SHELL的好帮手啊

Program audio and sound for Linux using this practical, how-to guide. You will learn how to use DSPs, sampled audio, MIDI, karaoke, streaming audio, and more. Linux Sound Programming takes you through the layers of complexity involved in programming the Linux sound system. You’ll see the large variety of tools and approaches that apply to almost every aspect of sound. This ranges from audio codecs, to audio players, to audio support both within and outside of the Linux kernel. What You'll LearnWork with sampled audio Handle Digital Signal Processing (DSP) Gain knowledge of MIDI Build a Karaoke-like application Handle streaming audio Who This Book Is For Experienced Linux users and programmers interested in doing multimedia with Linux.

3d game engine programming 清晰 版，大小不到十兆，不想有些版本200多兆

Linux程序设计教学课件：Ch2 Shell Programming.pdf

Linux程序设计

IE598NH-lecture-5-Two stage stochastic linear programming.pdfIE598NH-lecture-5-Two stage stochastic linear programming.pdf

openGL 程序指导书 中文译本完整版 红宝书 本书由李军和徐波译，原作者为Dava Shreiner，是ARM公司图形技术总监，长期担任SGI核心OpenGL组的成员。

AIX 5L Korn and bash Shell Programming

Python and Tkinter Programming.pdf Python and Tkinter Programming.pdf

CUDA programming: a developer's guide to parallel computing with GPUs. by Shane Cook. Over the past five years there has been a revolution in computing brought about by a company that for successive years has emerged as one of the premier gaming hardware manufacturersdNVIDIA. With the introduction of the CUDA (Compute Unified Device Architecture) programming language, for the first time these hugely powerful graphics coprocessors could be used by everyday C programmers to offload computationally expensive work. From the embedded device industry, to home users, to supercomputers, everything has changed as a result of this. One of the major changes in the computer software industry has been the move from serial programming to parallel programming. Here, CUDA has produced great advances. The graphics processor unit (GPU) by its very nature is designed for high-speed graphics, which are inherently parallel. CUDA takes a simple model of data parallelism and incorporates it into a programming model without the need for graphics primitives. In fact, CUDA, unlike its predecessors, does not require any understanding or knowledge of graphics or graphics primitives. You do not have to be a games programmer either. The CUDA language makes the GPU look just like another programmable device. Throughout this book I will assume readers have no prior knowledge of CUDA, or of parallel programming. I assume they have only an existing knowledge of the C/C++ programming language. As we progress and you become more competent with CUDA, we’ll cover more advanced topics, taking you from a parallel unaware programmer to one who can exploit the full potential of CUDA. For programmers already familiar with parallel programming concepts and CUDA, we’ll be discussing in detail the architecture of the GPUs and how to get the most from each, including the latest Fermi and Kepler hardware. Literally anyone who can program in C or C++ can program with CUDA in a few hours given a little training. Getting from novice CUDA programmer, with a several times speedup to 10 times–plus speedup is what you should be capable of by the end of this book. The book is very much aimed at learning CUDA, but with a focus on performance, having first achieved correctness. Your level of skill and understanding of writing high-performance code, especially for GPUs, will hugely benefit from this text. This book is a practical guide to using CUDA in real applications, by real practitioners. At the same time, however, we cover the necessary theory and background so everyone, no matter what their background, can follow along and learn how to program in CUDA, making this book ideal for both professionals and those studying GPUs or parallel programming.