![]() In the case of image processing, for example, you map the image onto the threads as shown in the following figure and apply a function to each pixel. In terms of the above image, a grid, block, and thread are as follows.Ĭhoosing whether to have a one-, two-, or three-dimensional thread configuration is dependent on the problem. The following shows a typical two-dimensional CUDA thread configuration.Įach grid contains multiple blocks, and each block contains multiple threads. Unlike the message-passing or thread-based parallel programming models, CUDA programming maps problems on a one-, two-, or three-dimensional grid. The following sections will discuss this, along with how threads are partitioned for execution. The reason CUDA can launch thousands of threads all lies in its hardware architecture. CUDALink's equivalence to CUDALaunch is CUDAFunction. The above launches 10000 ×10000 threads, passes their indices to each thread, applying the function to InputData, and places the results in OutputData. If the following is your computation:ĬUDALaunch From a high-level standpoint, the problem is first partitioned onto hundreds or thousands of threads for computation. This is done by utilizing all levels of the NVIDIA architecture stack.ĬUDA's programming is based on the data parallel model. With the Wolfram Language, you only need to write CUDA kernels. When using the Wolfram Language, you need not worry about many of the steps. CUDALink aims at making GPU programming easy and accelerating the adoption. While programming the GPU has been around for many years, difficulty in programming it had made adoption limited. The Common Unified Device Architecture (CUDA) was developed by NVIDIA in late 2007 as a way to make the GPU more general. In the end, many applications written using CUDALink are demonstrated. This document describes the GPU architecture and how to write a CUDA kernel. You can configure Barracuda CloudGen Firewall SSL VPN and CudaLaunch on iOS and Android to use client certificate authentication.įor more information, see How to Configure Client Certificate Authentication for the SSL VPN and How to Configure CudaLaunch for Mobile with Client Certificate Authentication.Loads a CUDA function into the Wolfram LanguageĬUDA programming in the Wolfram Language. When the time limit is reached, all existing firewall sessions matching this rule are terminated.įor more information, see How to Create and Activate a Dynamic Access Rule and How to Activate Dynamic Firewall Rules for Remote Connections via SSL VPN. CudaLaunch allows users with the necessary permissions to enable (with or without time limit) or disable the dynamic rule. SSL VPN Dynamic Firewall Rulesĭynamic firewall rules allow administrators to temporarily enable access rules. ![]() Important or frequently used Web Forwards can be marked as favorites.įor more information, see How to Configure a Generic Proxied Web App, How to Configure an Outlook Web Access Web App and How to Configure a SharePoint Web App. SSL VPN AppsĪ searchable list of Web Forwards is displayed when logging in to CudaLaunch. You can create multiple VPN Template Resources and restrict them per group as needed.įor more information, see How to Configure VPN Group Policies in the SSL VPN. CudaLaunch will automatically present the VPN templates to the user. Create a VPN Template on the SSL VPNĮxport the VPN configuration file for the VPN Group Policy and then create a VPN Template resource for the SSL VPN. Create an IPsec PSK group policy and verify that both IPsec Client and Barracuda Client are enabled in the Group Policy Conditions.įor more information, see How to Configure a Client-to-Site VPN Group Policy or Example - Client-to-Site IKEv1 IPsec VPN with PSK. You must configure a client-to-site group policy that is compatible with both Android and iOS devices. Due to differences in the mobile operating systems, the Android version of CudaLaunch uses the Barracuda VPN client with the TINA protocol, whereas CudaLaunch on iOS manages the built-in iOS IPsec client. By default, the first VPN template is used to connect to the VPN service. To use the full device VPN, you must create a client-to-site configuration and a VPN Template Resource in the SSL VPN in order to push the configuration to the mobile devices. For testing purposes one concurrent SSL VPN and CudaLaunch connection is included in the base license. ![]() To use CudaLaunch an Advanced Remote Access subscription is required. CudaLaunch supports the same SSL VPN features as the web portal and resources using SSL Tunnels. Enable the SSL VPN to allow mobile apps to connect.
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