You can use the -enable-remote-profiling command-line option to enable the system that hosts VTune server as the performance profiling target. This action is controlled by the toForwardPorts setting, which is enabled by default. The Remote - SSH extension automatically forwards these ports through the SSH tunnel. The setup described in Option 1 relies on the functionality of the VS Code Remote - SSH extension to watch port numbers used by processes that are started through the VS Code terminal. For more information, see Set Up Analysis Target. Set the target application path and any command-line arguments. Your remote machine (running the Intel® VTune™ Profiler server) is selected as the target system by default since you ran the server with -enable-server-profiling option. Once you set the passphrase, the Intel® VTune™ Profiler welcome screen opens.Ĭonfigure an analysis. Also, your browser stores a secure HTTP cookie so that you do not need to enter the passphrase each time you open the VTune GUI. The hash of the passphrase is persisted on the server. Other users cannot access your Intel® VTune™ Profiler server without the passphrase. When you open this URL on a browser, Intel® VTune™ Profiler server prompts you to set a passphrase. When you run VTune server for the first time, the URL that it displays should contain a one-time-token. For more information on transport security, see Set Up Transport Security. You can proceed safely without installing the certificate because the SSH tunnel provides protection from Man-in-the-Middle (MitM) attacks. When you open the VTune GUI, your web browser may prompt you about the VTune server self-signed certificate. Whether you chose Option 1 or Option 2, complete the setup by following these steps: Use Intel® VTune™ Profiler Server on a Remote System via SSH Terminal Finish Setup Usage Considerations Using Intel® VTune™ Profiler Server in HPC Clusters Profiling in a Singularity* Container Profiling Linux*, Android*, and QNX* System Boot Time NET* Core Application Profiling Applications in Amazon Web Services* (AWS) EC2 Instances Enabling Performance Profiling in GitLab* CI Configuring a Hyper-V* Virtual Machine for Hardware-Based Hotspots Analysis Profiling an Application for Performance Anomalies (NEW) Profiling an OpenMP* Offload Application running on a GPU (NEW) Profiling a SYCL* Application running on a GPU Using the Command-Line Interface to Analyze the Performance of a SYCL* Application running on a GPU (NEW) Profiling an FPGA-driven SYCL* Application Profiling Hardware Without Intel Sampling Drivers Profiling MPI Applications Profiling Docker* Containers Profiling a Remote Target Through a Proxy Server (NEW) Using Intel® VTune™ Profiler Server with Visual Studio Code and Intel® DevCloud for oneAPI (NEW) Ingredients Setup Overview Option 1: Use Intel® VTune™ Profiler Server for Remote Development with Visual Studio Code Option 2. Analyzing Hot Code Paths Using Flame Graphs (NEW) Improving Hotspot Observability in a C++ Application Using Flame Graphs Profiling Games built with Unity* (NEW) Profiling Games built with Unreal Engine* (NEW) Profiling Java Applications as a Remote User (NEW) Profiling JavaScript* Code in Node.js* Measuring Performance Impact of NUMA in Multi-Processor Systems (NEW) Analyzing CPU and FPGA (Intel® Arria® 10 GX) Interaction Profiling a.
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