![]() CUDA Toolkit 4. 0 | NVIDIA Developer. Easier Application Porting. Share GPUs across multiple threads. Use all GPUs in the system concurrently from a single host thread. No- copy pinning of system memory, a faster alternative to cuda. Malloc. Host(). C++ new/delete and support for virtual functions. Support for inline PTX assembly. ![]() Thrust library of templated performance primitives such as sort, reduce, etc. NVIDIA Performance Primitives (NPP) library for image/video processing. Layered Textures for working with same size/format textures at larger sizes and higher performance. Faster Multi- GPU Programming. Unified Virtual Addressing. GPUDirect v. 2. 0 support for Peer- to- Peer Communication. New & Improved Developer Tools. Automated Performance Analysis in Visual Profiler. C++ debugging in CUDA- GDB for Linux and Mac. OS. GPU binary disassembler for Fermi architecture (cuobjdump)Parallel Nsight 2. Windows developers with new debugging and profiling features. Watch the CUDA Toolkit 4. Feature and Overview Webinar (or just the slides) for an overview of some of the exciting new features of this release. Check out the NEW CUDA 4. Math Library Performance Review Find all the latest versions of other Libraries and Tools on our Tools & Eco. System Page. Please download the lastest CUDA Toolkit 4. Errata Update. The latest released NVIDIA Drivers are always available at www. For previous releases, see the CUDA Toolkit Release Archive. Get yourself fully trained- check out the latest CUDA Webinars. Become a CUDA Registered Developer, report bugs, engage with NVIDIA engineering. Jump to: [Windows][ Linux ] [ Mac. OS ] Windows 7, VISTA, Windows XPDownloads. Developer Drivers for Win. XP (2. 70. 8. 1)Support for XP on notebooks is being phased out and is not available for this release. See Release Notes and Getting Started Guides for more information. Developer Drivers for Win. Vista and Win. 7 (2. Notebook Developer Drivers for Win. Vista and Win. 7 (2. CUDA Toolkit. C/C++ compiler. Visual Profiler. GPU- accelerated BLAS library. GPU- accelerated FFT library. Quick Start Guide This guide provides the minimal first-steps instructions for installation and verifying CUDA on a standard system. Installation Guide Windows. ESXi and vCenter Server 5.1 Documentation VMware vSphere ESXi and vCenter Server 5.1 Documentation vSphere Installation and Setup Updated Information. This topic describes how to install the SQL Server Tools on Linux. All channels may be run in parallel -- they install into distinct directories and use dedicated User Data directories. GPU- accelerated Sparse Matrix library. GPU- accelerated RNG library. Additional tools and documentation. NEW* CUDA Toolkit 4. Build Customization BUG FIX Update. Fixes error message "$(CUDABuild. Tasks. Path) property is not valid"download. GPU Computing SDK - complete package including all code samples. Parallel Nsight 2. Learn about additional tools, libraries, and more…CUDA Ecosystem. CUDA Tools SDK (APIs for 3rd party performance analysis tools and cluster management solutions)3. Linux. Downloads. Developer Drivers for Linux (2. CUDA Toolkit. C/C++ compiler. CUDA- GDB debugger. Visual Profiler. GPU- accelerated BLAS library. GPU- accelerated FFT library. GPU- accelerated Sparse Matrix library. GPU- accelerated RNG library. Additional tools and documentationdocumentation. Visual Profiler Errata. CUDA Toolkit for Fedora 1. Visual Profiler_Patch)6. Visual Profiler Patch). CUDA Toolkit for Red. Hat Enterprise Linux 6. Visual Profiler Patch). CUDA Toolkit for Red. Hat Enterprise Linux 5. Visual Profiler Patch)6. Visual Profiler Patch). CUDA Toolkit for Red. Hat Enterprise Linux 4. Visual Profiler Patch). CUDA Toolkit for Ubuntu Linux 1. Visual Profiler Patch)6. Visual Profiler Patch). CUDA Toolkit for Open. SUSE 1. 1. 2. 32- bit, (Visual Profiler Patch)6. VP Patch - coming soon). CUDA Toolkit for SUSE Linux Enterprise Server 1. SP1. 32- bit, (Visual Profiler Patch)6. Visual Profiler Patch). GPU Computing SDK - complete package including all code samplesdownload browse online. Learn about additional tools, libraries, and more…CUDA Ecosystem.CUDA Tools SDK (APIs for 3rd party debuggers, performance analysis tools and cluster management solutions)3. Bible Bless E Software Study Swordfish here. Mac OS XDownloads.Developer Drivers (4.Mac. OS (requires OS ver.CUDA Toolkit (requires OS version 1. C/C++ compiler. CUDA- GDB debugger. Visual Profiler. GPU- accelerated BLAS library. GPU- accelerated FFT library. GPU- accelerated Sparse Matrix library. GPU- accelerated RNG library. Additional tools and documentationdownloaddocumentation. GPU Computing SDK - complete package including all code samplesdownload Browse Online. Learn about additional tools, libraries, and more…CUDA Ecosystem. CUDA Tools SDK (APIs for 3rd party debuggers and performance analysis tools)download. Get started with SQL Server 2. Docker. THIS TOPIC APPLIES TO: SQL Server on Windows. SQL Server on Linux. Azure SQL Database. Azure SQL Data Warehouse. Parallel Data Warehouse In this quick start tutorial, you use Docker to pull and run the SQL Server 2. Then connect with sqlcmd to create your first database and run queries. This image consists of SQL Server running on Linux based on Ubuntu 1. It can be used with the Docker Engine 1. Linux or on Docker for Mac/Windows. Note. This quick start specifically focuses on using the mssql- server- linux image. The Windows image is not covered, but you can learn more about it on the mssql- server- windows Docker Hub page. Prerequisites. Important. The default on Docker for Mac and Docker for Windows is 2 GB for the Moby VM, so you must change it to 4 GB. If you are running on Mac or Windows, use the following procedures to increase the memory. Increase Docker memory to 4 GB (Mac)The following steps increase the memory for Docker for Mac to 4 GB. Click the Docker logo on the top status bar. Select Preferences. Move the memory indicator to 4 GB or more. Click the restart button at the button of the screen. Increase Docker memory to 4 GB (Windows)The following steps increase the memory for Docker for Windows to 4 GB. Right- click on the Docker icon from the task bar. Click Settings under that menu. Click the Advanced Tab. Move the memory indicator to 4 GB or more. Click the Apply button. Pull and run the container image. Pull the SQL Server 2. Linux container image from Docker Hub. Tip. For Linux, depending on your system and user configuration, you might need to preface each docker command with sudo. Note. The command above pulls the SQL Server 2. GA container image. If you want to pull a specific image, you add a colon and the tag name (for example, microsoft/mssql- server- linux: rc. To see all available images, see the mssql- server- linux Docker hub page. To run the container image with Docker, you can use the following command from a bash shell (Linux/mac. OS): docker run - e 'ACCEPT_EULA=Y' - e 'MSSQL_SA_PASSWORD=< Your. Strong! Passw. 0rd> ' - e 'MSSQL_PID=Developer' - p 1. If you are using Docker for Windows, use the following command from an elevated Power. Shell command- prompt: docker run - e "ACCEPT_EULA=Y" - e "MSSQL_SA_PASSWORD=< Your. Strong! Passw. 0rd> " - e "MSSQL_PID=Developer" - p 1. Note. The only difference between the bash (Linux/mac. OS) example and the Power. Shell (Windows) example is single quotes versus double- quotes around the environment variables. The docker run command fails if you use the wrong one. Throughout the remainder of this topic, bash and Power. Shell code blocks are provided for convenience. If there is only one example, it works on all platforms, including Windows. The following table provides a description of the parameters in the previous docker run example: Parameter. Description- e 'ACCEPT_EULA=Y'Set the ACCEPT_EULA variable to any value to confirm your acceptance of the End- User Licensing Agreement. Required setting for the SQL Server image.- e 'MSSQL_SA_PASSWORD=< Your. Strong! Passw. 0rd> 'Specify your own strong password that is at least 8 characters and meets SQL Server's password requirements. Required setting for the SQL Server image.- e 'MSSQL_PID=Developer'Specifies the edition or product key. In this example, the freely licensed Developer Edition is used for non- production testing. For other values, see Configure SQL Server settings with environment variables on Linux.- p 1. Map a TCP port on the host environment (first value) with a TCP port in the container (second value). In this example, SQL Server is listening on TCP 1. Specify a custom name for the container rather than a randomly generated one. If you run more than one container, you can't reuse this same name. The SQL Server 2. Linux container image. To view your Docker containers, use the docker ps command. You should see output similar to the following screenshot: If the STATUS column shows a status of Up, then SQL Server is running in the container and listening on the port specified in the PORTS column. If the STATUS column for your SQL Server container shows Exited, see the Troubleshooting section of the configuration guide. The - h (host name) parameter is also useful, but it is not used in this tutorial for simplicity. This changes the internal name of the container to a custom value. This is the name you'll see returned in the following Transact- SQL query: SELECT @@SERVERNAME. SERVERPROPERTY('Computer. Name. Physical. Net. BIOS'). SERVERPROPERTY('Machine. Name'). SERVERPROPERTY('Server. Name'). Setting - h and - -name to the same value is a good way to easily identify the target container. Change the SA password. The SA account is a system administrator on the SQL Server instance that gets created during setup. After creating your SQL Server container, the MSSQL_SA_PASSWORD environment variable you specified is discoverable by running echo $MSSQL_SA_PASSWORD in the container. For security purposes, change your SA password. Choose a strong password to use for the SA user. Use docker exec to run sqlcmd to change the password using Transact- SQL. Replace < Your. Strong! Passw. 0rd> and < Your. New. Strong! Passw. S localhost - U SA - P '< Your. Strong! Passw. 0rd> ' \. Q 'ALTER LOGIN SA WITH PASSWORD="< Your. New. Strong! Passw. S localhost - U SA - P "< Your. Strong! Passw. 0rd> " `. Q "ALTER LOGIN SA WITH PASSWORD='< Your. New. Strong! Passw. Black And Decker Lithium Dustbuster Manual here. Connect to SQL Server. The following steps use the SQL Server command- line tool, sqlcmd, inside the container to connect to SQL Server. Use the docker exec - it command to start an interactive bash shell inside your running container. In the following example sql. Once inside the container, connect locally with sqlcmd. Sqlcmd is not in the path by default, so you have to specify the full path./opt/mssql- tools/bin/sqlcmd - S localhost - U SA - P '< Your. New. Strong! Passw. Tip. You can omit the password on the command- line to be prompted to enter it. If successful, you should get to a sqlcmd command prompt: 1>. Create and query data. The following sections walk you through using sqlcmd and Transact- SQL to create a new database, add data, and run a simple query. Create a new database. The following steps create a new database named Test. DB. From the sqlcmd command prompt, paste the following Transact- SQL command to create a test database: CREATE DATABASE Test. DB. On the next line, write a query to return the name of all of the databases on your server: SELECT Name from sys. Databases. The previous two commands were not executed immediately. You must type GO on a new line to execute the previous commands: GO. Insert data. Next create a new table, Inventory, and insert two new rows. From the sqlcmd command prompt, switch context to the new Test. DB database: USE Test. DB. Create new table named Inventory: CREATE TABLE Inventory (id INT, name NVARCHAR(5. INT). Insert data into the new table: INSERT INTO Inventory VALUES (1, 'banana', 1. INSERT INTO Inventory VALUES (2, 'orange', 1. Type GO to execute the previous commands: GO. Select data. Now, run a query to return data from the Inventory table. From the sqlcmd command prompt, enter a query that returns rows from the Inventory table where the quantity is greater than 1. SELECT * FROM Inventory WHERE quantity > 1. Execute the command: GO. Exit the sqlcmd command prompt. To end your sqlcmd session, type QUIT: QUIT. To exit the interactive command- prompt in your container, type exit. Your container continues to run after you exit the interactive bash shell. Connect from outside the container. You can also connect to the SQL Server instance on your Docker machine from any external Linux, Windows, or mac. OS tool that supports SQL connections. The following steps use sqlcmd outside of your container to connect to SQL Server running in the container. These steps assume that you already have the SQL Server command- line tools installed outside of your container. The same principals apply when using other tools, but the process of connecting is unique to each tool. Find the IP address for the machine that hosts your container. On Linux, use ifconfig or ip addr. On Windows, use ipconfig. Run sqlcmd specifying the IP address and the port mapped to port 1. In this example, that is port 1. S 1. 0. 3. 2. 4,1. U SA - P '< Your. New. Strong! Passw. S 1. 0. 3. 2. 4,1. U SA - P "< Your. New. Strong! Passw. Run Transact- SQL commands. When finished, type QUIT.
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