However, In Stack Overflow's 2016 developer survey, OS X topped the most used Desktop Operating System, followed by Windows 7 and then Linux. StackOverflow says: 'Last year, Mac. For software development, Linux is vastly better. Software development on MacOS X is tedious in comparison. The basic Unix layer hasn't been maintained properly for over a decade now. Seriously, it's FreeBSD from 2006-7 with no updates.

Release Notes

The Release Notes for the CUDA Toolkit.

EULA

The End User License Agreements for the NVIDIA CUDA Toolkit, the NVIDIA CUDA Samples, the NVIDIA Display Driver, and NVIDIA NSight (Visual Studio Edition).

Installation Guides

Quick Start Guide

This guide provides the minimal first-steps instructions for installation and verifying CUDA on a standard system.

Installation Guide Windows

This guide discusses how to install and check for correct operation of the CUDA Development Tools on Microsoft Windows systems.

Installation Guide Linux

This guide discusses how to install and check for correct operation of the CUDA Development Tools on GNU/Linux systems.

Programming Guides

Programming Guide

This guide provides a detailed discussion of the CUDA programming model and programming interface. It then describes the hardware implementation, and provides guidance on how to achieve maximum performance. The appendices include a list of all CUDA-enabled devices, detailed description of all extensions to the C++ language, listings of supported mathematical functions, C++ features supported in host and device code, details on texture fetching, technical specifications of various devices, and concludes by introducing the low-level driver API.

Best Practices Guide

This guide presents established parallelization and optimization techniques and explains coding metaphors and idioms that can greatly simplify programming for CUDA-capable GPU architectures. The intent is to provide guidelines for obtaining the best performance from NVIDIA GPUs using the CUDA Toolkit.

Maxwell Compatibility Guide

This application note is intended to help developers ensure that their NVIDIA CUDA applications will run properly on GPUs based on the NVIDIA Maxwell Architecture. This document provides guidance to ensure that your software applications are compatible with Maxwell.

Pascal Compatibility Guide

This application note is intended to help developers ensure that their NVIDIA CUDA applications will run properly on GPUs based on the NVIDIA Pascal Architecture. This document provides guidance to ensure that your software applications are compatible with Pascal.

Volta Compatibility Guide

This application note is intended to help developers ensure that their NVIDIA CUDA applications will run properly on GPUs based on the NVIDIA Volta Architecture. This document provides guidance to ensure that your software applications are compatible with Volta.

Turing Compatibility Guide

This application note is intended to help developers ensure that their NVIDIA CUDA applications will run properly on GPUs based on the NVIDIA Turing Architecture. This document provides guidance to ensure that your software applications are compatible with Turing.

NVIDIA Ampere GPU Architecture Compatibility Guide

This application note is intended to help developers ensure that their NVIDIA CUDA applications will run properly on GPUs based on the NVIDIA Ampere GPU Architecture. This document provides guidance to ensure that your software applications are compatible with NVIDIA Ampere GPU architecture.

Kepler Tuning Guide

Kepler is NVIDIA's 3rd-generation architecture for CUDA compute applications. Applications that follow the best practices for the Fermi architecture should typically see speedups on the Kepler architecture without any code changes. This guide summarizes the ways that applications can be fine-tuned to gain additional speedups by leveraging Kepler architectural features.

Maxwell Tuning Guide

Maxwell is NVIDIA's 4th-generation architecture for CUDA compute applications. Applications that follow the best practices for the Kepler architecture should typically see speedups on the Maxwell architecture without any code changes. This guide summarizes the ways that applications can be fine-tuned to gain additional speedups by leveraging Maxwell architectural features.

Pascal Tuning Guide

Pascal is NVIDIA's 5th-generation architecture for CUDA compute applications. Applications that follow the best practices for the Maxwell architecture should typically see speedups on the Pascal architecture without any code changes. This guide summarizes the ways that applications can be fine-tuned to gain additional speedups by leveraging Pascal architectural features.

Volta Tuning Guide

Volta is NVIDIA's 6th-generation architecture for CUDA compute applications. Applications that follow the best practices for the Pascal architecture should typically see speedups on the Volta architecture without any code changes. This guide summarizes the ways that applications can be fine-tuned to gain additional speedups by leveraging Volta architectural features.

Turing Tuning Guide

Turing is NVIDIA's 7th-generation architecture for CUDA compute applications. Applications that follow the best practices for the Pascal architecture should typically see speedups on the Turing architecture without any code changes. This guide summarizes the ways that applications can be fine-tuned to gain additional speedups by leveraging Turing architectural features.

NVIDIA Ampere GPU Architecture Tuning Guide

NVIDIA Ampere GPU Architecture is NVIDIA's 8th-generation architecture for CUDA compute applications. Applications that follow the best practices for the NVIDIA Volta architecture should typically see speedups on the NVIDIA Ampere GPU Architecture without any code changes. This guide summarizes the ways that applications can be fine-tuned to gain additional speedups by leveraging NVIDIA Ampere GPU Architecture's features.

PTX ISA

This guide provides detailed instructions on the use of PTX, a low-level parallel thread execution virtual machine and instruction set architecture (ISA). PTX exposes the GPU as a data-parallel computing device.

Developer Guide for Optimus

This document explains how CUDA APIs can be used to query for GPU capabilities in NVIDIA Optimus systems.

Video Decoder

NVIDIA Video Decoder (NVCUVID) is deprecated. Instead, use the NVIDIA Video Codec SDK (https://developer.nvidia.com/nvidia-video-codec-sdk).

PTX Interoperability

This document shows how to write PTX that is ABI-compliant and interoperable with other CUDA code.

Inline PTX Assembly

This document shows how to inline PTX (parallel thread execution) assembly language statements into CUDA code. It describes available assembler statement parameters and constraints, and the document also provides a list of some pitfalls that you may encounter.

CUDA Occupancy Calculator

The CUDA Occupancy Calculator allows you to compute the multiprocessor occupancy of a GPU by a given CUDA kernel.

CUDA API References

CUDA Runtime API

Fields in structures might appear in order that is different from the order of declaration.

CUDA Driver API

Fields in structures might appear in order that is different from the order of declaration.

CUDA Math API

The CUDA math API.

cuBLAS

The cuBLAS library is an implementation of BLAS (Basic Linear Algebra Subprograms) on top of the NVIDIA CUDA runtime. It allows the user to access the computational resources of NVIDIA Graphical Processing Unit (GPU), but does not auto-parallelize across multiple GPUs.

NVBLAS

The NVBLAS library is a multi-GPUs accelerated drop-in BLAS (Basic Linear Algebra Subprograms) built on top of the NVIDIA cuBLAS Library.

nvJPEG

The nvJPEG Library provides high-performance GPU accelerated JPEG decoding functionality for image formats commonly used in deep learning and hyperscale multimedia applications.

cuFFT

The cuFFT library user guide.

CUB

The user guide for CUB.

CUDA C++ Standard

The API reference for libcu++, the CUDA C++ standard library.

cuRAND

The cuRAND library user guide.

cuSPARSE

The cuSPARSE library user guide.

NPP

NVIDIA NPP is a library of functions for performing CUDA accelerated processing. The initial set of functionality in the library focuses on imaging and video processing and is widely applicable for developers in these areas. NPP will evolve over time to encompass more of the compute heavy tasks in a variety of problem domains. The NPP library is written to maximize flexibility, while maintaining high performance.

NVRTC (Runtime Compilation)

NVRTC is a runtime compilation library for CUDA C++. It accepts CUDA C++ source code in character string form and creates handles that can be used to obtain the PTX. The PTX string generated by NVRTC can be loaded by cuModuleLoadData and cuModuleLoadDataEx, and linked with other modules by cuLinkAddData of the CUDA Driver API. This facility can often provide optimizations and performance not possible in a purely offline static compilation.

Thrust

The Thrust getting started guide.

cuSOLVER

The cuSOLVER library user guide.

PTX Compiler API References

PTX Compiler APIs

This guide shows how to compile a PTX program into GPU assembly code using APIs provided by the static PTX Compiler library.

Miscellaneous

CUDA Samples

This document contains a complete listing of the code samples that are included with the NVIDIA CUDA Toolkit. It describes each code sample, lists the minimum GPU specification, and provides links to the source code and white papers if available.

CUDA Demo Suite

This document describes the demo applications shipped with the CUDA Demo Suite.

CUDA on WSL

This guide is intended to help users get started with using NVIDIA CUDA on Windows Subsystem for Linux (WSL 2). The guide covers installation and running CUDA applications and containers in this environment.

Multi-Instance GPU (MIG)

This edition of the user guide describes the Multi-Instance GPU feature of the NVIDIA® A100 GPU.

CUDA Compatibility

This document describes CUDA Compatibility, including CUDA Enhanced Compatibility and CUDA Forward Compatible Upgrade.

CUPTI

The CUPTI-API. The CUDA Profiling Tools Interface (CUPTI) enables the creation of profiling and tracing tools that target CUDA applications.

Debugger API

The CUDA debugger API.

GPUDirect RDMA

A technology introduced in Kepler-class GPUs and CUDA 5.0, enabling a direct path for communication between the GPU and a third-party peer device on the PCI Express bus when the devices share the same upstream root complex using standard features of PCI Express. This document introduces the technology and describes the steps necessary to enable a GPUDirect RDMA connection to NVIDIA GPUs within the Linux device driver model.

vGPU

vGPUs that support CUDA.

Tools

NVCC

This is a reference document for nvcc, the CUDA compiler driver. nvcc accepts a range of conventional compiler options, such as for defining macros and include/library paths, and for steering the compilation process.

CUDA-GDB

The NVIDIA tool for debugging CUDA applications running on Linux and Mac, providing developers with a mechanism for debugging CUDA applications running on actual hardware. CUDA-GDB is an extension to the x86-64 port of GDB, the GNU Project debugger.

CUDA-MEMCHECK

CUDA-MEMCHECK is a suite of run time tools capable of precisely detecting out of bounds and misaligned memory access errors, checking device allocation leaks, reporting hardware errors and identifying shared memory data access hazards.

Compute Sanitizer

The user guide for Compute Sanitizer.

Nsight Eclipse Plugins Installation Guide

Nsight Eclipse Plugins Installation Guide

Nsight Eclipse Plugins Edition

Nsight Eclipse Plugins Edition getting started guide

Nsight Compute

The NVIDIA Nsight Compute is the next-generation interactive kernel profiler for CUDA applications. It provides detailed performance metrics and API debugging via a user interface and command line tool.

Profiler

This is the guide to the Profiler.

CUDA Binary Utilities

The application notes for cuobjdump, nvdisasm, and nvprune.

White Papers

Floating Point and IEEE 754

A number of issues related to floating point accuracy and compliance are a frequent source of confusion on both CPUs and GPUs. The purpose of this white paper is to discuss the most common issues related to NVIDIA GPUs and to supplement the documentation in the CUDA C++ Programming Guide.

Incomplete-LU and Cholesky Preconditioned Iterative Methods

In this white paper we show how to use the cuSPARSE and cuBLAS libraries to achieve a 2x speedup over CPU in the incomplete-LU and Cholesky preconditioned iterative methods. We focus on the Bi-Conjugate Gradient Stabilized and Conjugate Gradient iterative methods, that can be used to solve large sparse nonsymmetric and symmetric positive definite linear systems, respectively. Also, we comment on the parallel sparse triangular solve, which is an essential building block in these algorithms.

Application Notes

CUDA for Tegra

This application note provides an overview of NVIDIA® Tegra® memory architecture and considerations for porting code from a discrete GPU (dGPU) attached to an x86 system to the Tegra® integrated GPU (iGPU). It also discusses EGL interoperability.

Compiler SDK

libNVVM API

The libNVVM API.

libdevice User's Guide

The libdevice library is an LLVM bitcode library that implements common functions for GPU kernels.

NVVM IR

NVVM IR is a compiler IR (internal representation) based on the LLVM IR. The NVVM IR is designed to represent GPU compute kernels (for example, CUDA kernels). High-level language front-ends, like the CUDA C compiler front-end, can generate NVVM IR.

Mac vs. Windows vs. Linux

Three operating systems – Windows, Macintosh, and Linux – dominate the world of computing today. But what sets them apart?

History

For Linux And Mac Os In Development Process

The first Windows system was released in 1985. Originally, it was just a graphical user interface on top of MS-DOS – a state of affairs that lasted until the release of Windows 95, when MS-DOS products were integrated into Windows. Windows 95 was a huge departure from the previous systems and was the first major step in Window’s transition from GUI to operating system.

The Apple Macintosh system is a little older than Windows, having first been released in 1984. From the start, it was an entirely graphical operating system, and from quite an early stage became popular among the earliest computer graphic designers. In 2005, Apple changed the design and structure of Mac OS, moving from the IBM-made PowerPC CPU architecture to the same Intel x86-based architecture as used in PCs. This heralded the transition from “Classic” Mac OS to the current OS X series. The design change meant Mac became a Unix-based operating system, like the next OS I will cover.

Linux has the unlikely origin of being the hobby project of Finnish university student Linus Torvalds. He was unsatisfied with an existing Unix-like academic operating system – with limited licensing – named Minix, and decided he could do better (and make it free, open-source software). The resulting system was eventually named after Torvalds. The Linux kernel was first released independently in 1991, designed to be used with GNU software. GNU developers eventually integrated their software into Linux to create an OS. Linux is available in many forms to suit many needs, from consumer-oriented systems for home use to distributions for use in specific industries.

Check out this awesome infograph on Mac vs Pc by iTok. ——->>>

Benefits

The Windows series of operating systems have the obvious benefit of market ubiquity. For most people, Windows will be extremely familiar and therefore easy to use; Windows is the “standard” operating system bundled with new PCs. This means that the vast majority of software, hardware, support and training available is designed with Windows compatibility primarily in mind. The overwhelming market dominance of the Windows operating system has shaped the way consumers relate to and think about OS’s and GUI’s – “taskbar” “start menu” and “desktop” all entered the common lexicon following the immense popularity of Windows 95.

OS X is known for its excellent, intuitive user interface. Its main advantage continues to be that, due to inevitably having fewer users than Windows, there are far fewer viruses written for the system making it less vulnerable to attack. As well as being secure, the system is very stable, whilst maintaining high levels of performance – an advantage considering the impressive range of professional applications available.

Linux has the immediate benefit of being free to obtain, and available for use without restrictions. It is open source with a large, supportive community building a seemingly infinite range of free applications for use on Linux machines. Many (many!) distributions of Linux are available, giving users the ability to choose one that suits their personal needs (then further customize it). Similar to OS X, Linux is less vulnerable to attack than a Windows PC, and Linux distributions are typically updated frequently – incredibly frequently compared to other operating systems – further enhancing their stability and security. Linux operating systems are perhaps the most widely ported – there are distributions used in a wide range of devices from smartphones to TiVo.

Differences

Windows is designed to run on PCs, whether bought new or built cheaply, so hardware costs are essentially determined by the consumer. However, the cost of buying the latest version of Windows can be prohibitive (Windows XP is still the most widely used version), and the restrictive licensing inevitably forces each user to purchase a copy as they cannot be shared. Coupled with the similarly inevitable cost of purchasing the also-ubiquitous Microsoft Office suite and it is easy to see how users may prefer to simply wait until they need to buy a new PC bundled with Microsoft software.

Despite being Unix-based, OS X is also proprietary software. Furthermore, users are forced to purchase Apple hardware if they wish to use it; Apple computers remain much more expensive than PCs.

Linux may be the cheapest, most easily available and customizable of the three, but the continued dominance of Windows (not to mention the fact it comes pre-installed on most machines) often deters home users from changing to this unfamiliar platform. Additionally, while Linux may have a large number of community-sourced applications available, it does not offer as many professional quality one as the other systems. Minority use means some third party software (such as popular PC games) is yet to have a Linux release.

Popularity

Windows continues to be the most popular OS worldwide, with Microsoft estimated to be holding on to roughly 90% of desktop users. Windows still represents the extent of many home users’ experience with operating systems. Apple computers have gained in popularity in recent years, and the Mac OS remains popular with professionals – particularly those in creative industries such as graphic design and video editing – due to the quality and performance of programs such as Photoshop on OS X. The OS X system is also the basis for the iPhone iOS, giving many more users contact and experience with Apple systems. Linux may have the smallest share of home users, however commercial use is huge. Servers, mainframes and supercomputers commonly use Linux, as do the film industry, governments both nationally and locally, and many portable device manufacturers. As personal computers move away from the desktop and increasingly become portable, adoption of other operating systems will surely follow.

Every now and then, I get clients who ask me for recommendations on what laptop or computer they should get. I figured this would be a great place to list some of my favorites. Now keep in mind, it really depends on your needs! There are so many different choices out there that it’s hard to say my recommendations will be right for YOU.

Apple MacBook Air
This is honestly the best laptop I’ve ever owned. It is so damn sexy. While it’s super portable (weighing 3 pounds and measuring .68 inches at its thickest), this is a powerful laptop. Because of its physical size, it may not have as much hard drive space as most computers (256 gb at the most), but you’ll find it has plenty. The battery life is crazy awesome. I can even let it sleep for days and open it to find plenty of battery life left.

Mac Os Linux Download

Samsung Series 5 550 Chromebook
Now, this laptop DOESN’T have Windows installed, but I thought I’d list it here anyway. In case you didn’t know, I love Google and their products! What makes the Chromebook unique is that it is easy and fast to use. Your computer doesn’t really “get old” because with the automatic updates, your Chromebook “keeps getting better and better”. The computer also features automatic updates, no blue screen, built-in virus protection, super fast booting and start up, and more! Check it out.