Nvidia visual profiler не работает

Не работает visual profiler (internal error)

Есть CUDA 7.0, Windows 8.1 и MS VS 13
Запускаю профайлер, в нем выбираю приложение .exe
Когда пытаюсь «Run applications to collect metric and events», выскакивает ошибка.
Когда пытаюсь «Examine GPU usage», выскакивает ошибка.
Когда пытаюсь «Examine Individual Kernels», выскакивает ошибка.
Даже на самых простых приложений типа как на картинке ниже.

Видеокарта GeForce 610M (2.1)
Еще постоянно предупреждение выскакивает, что Unified Memory доступна только на 3.0 и старше.

Пробовал сносить 7.0 и устанавливать 7.5 куду, там были траблы с Path. Хотя их быть не должно, все написано верно. 😐
Сейчас опять снес все, что связано с NVIDIA и 7.5, и поставил 7.0

Помогите. ((((

Помощь в написании контрольных, курсовых и дипломных работ здесь.

Не работает самописный шаблон для J1.7 — 500 Internal Server Error
Уважаемые пользователи форума, помогите пожалуйста. Уже пухнет голова. Те ответы, которые здесь и.

Не работает ADODB.Stream: HTTP 500 — Internal server error Internet Explorer
Помогите не работает почему-то. Вот код взял у вас на форуме: function saveToFile(strFName.

«internal consistecy error » в Visual FoxPro
Есть база данных, написанная на 5 VF и когда команда Seek обращается к таблице 16 раз, программа.

Error 1 fatal error LNK1000: Internal error during IncrBuildImage ModalMnd
Ребята помогите пожалуиста разобраться с ошибкой ! только начал изучать WinApi ! Visual studio 8.

HTTP Error 500.19 — Internal Server Error — Read permisions
http://ScrnSht.com/nxevbh думаю суть проблемы понятна попгуглив я накопал что надо бы поставить.

При компиляции выдает ошибку [Fatal Error] Unit4.pas(10): Internal error: SY576
При компиляции выдает ошибку Unit4.pas(10): Internal error: SY576 и выделяет строку .

C++ CodeDOM parser error: Line: 80, Column: 15 — Internal Error
Пробую связывать данные, созданные в дополнительных заголовочных файлах, с главным заголовочным.

1>LINK : fatal error LNK1000: Internal error during IncrBuildImage
периодически возникает в VS2008 1>LINK : fatal error LNK1000: Internal error during.

Network Error: 500 Internal Server Error
на локальной тачке на денвере все работает гут, а вот закидываю на сервер и ошибка 500. в чем.

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sonots / nvvp.md

Usually, located at /usr/local/cuda/bin

I prefer to use —print-gpu-trace.

On GPU machine, run

Copy prof.nvvp into your local machine

Then, run nvvp (nvidia visual profiler) on your local machine:

It works more comfortably than X11 forwarding or something.

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sonots commented Jul 11, 2017 •

For macOS: Install cuda toolkit for macOS. nvvp is included in it. Run nvvp command on console. You don’t need GPU on your macOS.

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sonots commented Jul 21, 2017 •

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sonots commented Jul 21, 2017 •

An example of nvprof output:

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sonots commented Oct 19, 2017 •

An example of nvprof result:

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sonots commented Oct 19, 2017 •

An example of nvprof —print-gpu-trace result:

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sonots commented Oct 19, 2017 •

An example of nvvp result:

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shizukanaskytree commented Aug 10, 2018

Thank you for your post!

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rohith14 commented Nov 1, 2018

Hi,
I get «No kernels profiled» as seen shown below. Any idea?

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NVIDIA Parallel Nsight Vs Visual Profiler

I am working with CUDA on the windows platform. On the windows platform we have access to both Parallel Nsight and Visual Profiler. Both are pretty good but then they have almost similar features for profiling and tracing. Can someone say me how are they both different and which one is better for the windows platform ?? I will basically be needing a tool for profiling.

3 Answers 3

Nsight Visual Studio Edition 2.2 offers the following advantages over the Visual Profiler:

Integration into Visual Studio 2008 SP1 and 2010 (requires Professional Edition as VS Express Edition does not support integration packages).

Local and remote analysis sessions. Remote sessions can also be configured to copy the application and resources to the remote system.

Collect information from a target application or from a process tree.

Report views support more advanced grouping and filtering. Data tables can be exported to excel.

Trace OS activity including process, thread, and module lifetime, thread context switching, thread wait reasons, CPU utilization, process CPU utilization, and thread utilization.

Collect API and GPU work trace for CUDA, OpenGL 2.x-3.x, DirectX 9-11, and OpenCL 1.1 and show all information on the timeline.

Collection of call stack traces on all traced API calls or only when traced API calls return errors.

CUDA software counters to show allocated memory per context.

Additional control over what information is traced. This is critical as tracing too much information can cause the application to become CPU bound.

Timeline and tree display for user annotations from NVIDIA Tools Extensions Library and D3D Performance Markers.

CUDA PROFILING ACTIVITY

The CUDA profiler provides a method to capture your kernel and replay it many times transparent to your application. This allows collection of profiling data in non-deterministic applications and with only 1 launch of your applications. The Visual Profiler

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NVIDIA Visual Profiler

The NVIDIA Visual Profiler is a cross-platform performance profiling tool that delivers developers vital feedback for optimizing CUDA C/C++ applications. First introduced in 2008, Visual Profiler supports all 350 million+ CUDA capable NVIDIA GPUs shipped since 2006 on Linux, Mac OS X, and Windows. The NVIDIA Visual Profiler is available as part of the CUDA Toolkit.

Note that NVIDIA® CUDA Toolkit 11.0 (and later) no longer supports development or running applications on macOS. While there are no tools which use macOS as a target environment, NVIDIA is making a macOS host version of Visual Profiler available from which you can launch profiling sessions on supported target platforms. You may download this and other macOS tools using the button below.

Overview

• Focus on the information that matters
  Quickly identify potential performance bottleneck issues in your applications using highly configurable tables and graphical views
• Automated performance analysis
  Perform automated analysis of your application to identify performance bottlenecks and get optimization suggestions that can be used to improve performance
• Unified CPU and GPU Timeline
  View CUDA activity occurring on both CPU and GPU in a unified time line, including CUDA API calls, memory transfers and CUDA launches.
• CUDA API trace
  View all memory transfers, kernel launches, and other API functions on the same timeline
• Drill down to raw data
  Gain low-level insights by looking at performance metrics collected directly from GPU hardware counters and software instrumentation.
• Compare results across multiple sessions
  Confirm performance improvements by comparing against previous sessions
• Analyze data collected from remote systems
  Use the command line profiler using environment variables to collect data from multiple systems and analyze the results in Visual Profiler
• CUDA Dynamic Parallelism
  View timeline for applications that use CUDA Dynamic Parallelism including both host-launched and device-launched kernels and the parent-child relationship between kernels.
• Guided Application Analysis
  Use the guided analysis mode has to get step-by-step analysis and optimization guidance. The analysis results now include graphical visualizations to more clearly indicate the optimization opportunities.
• Power, thermal, and clock profiling
  Observe how GPU power, thermal, and clock values vary during application execution

The latest version of Visual Profiler with support for both CUDA C/C++ applications is available with the CUDA Toolkit and is supported on all platforms supported by the CUDA Toolkit.

Developers should be sure to check out NVIDIA Nsight Systems for our next generation profiling tool with Linux, Windows, macOS, PowerPC, and Arm support. Be sure to review our tool migration recommendations to make your transition easier.

For development and debugging on Windows, see Nsight Visual Studio Edition and NVIDIA Nsight Systems Visual Studio integration with NVIDIA Nsight Integration.

For more information on the Visual Profiler and other CUDA development tools:

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NVIDIA Nsight Integration

NVIDIA Nsight Integration (highlighted) under the Nsight menu

NVIDIA Nsight Developer Tools Integration for Visual Studio

NVIDIA Nsight Integration is a Visual Studio extension that allows you to access the power of the following NVIDIA Nsight standalone tools from within Visual Studio.

• Nsight Compute : CUDA application interactive kernel profiler
• Nsight Graphics : Graphics application frame debugger and profiler
• Nsight Systems : System-wide performance analysis tool

When any of these tools are installed along with NVIDIA Nsight Integration , these tools will appear under the NVIDIA ‘ Nsight ‘ menu in the Visual Studio menu bar.

Revision History | Documentation

NVIDIA Nsight Integration is freely offered through the Microsoft Visual Studio Marketplace

Key Features

• Nsight standalone tools activity commands are now under the ‘Nsight’ menu, for quick access from within Visual Studio.
• When launched, Nsight standalone tool activities are auto-populated with Visual Studio project setting, providing an improved development workflow.
• Key bindings provide quick launching of activities.
• Visibility control options also you to individually hide and show the Nsight tools that you’ve installed.
• Available for use on Visual Studio 2019, 2017, and 2015 [1] .

[1] As of Nsight™ Visual Studio Edition 2020.2, released in September 2020, VS2015 support has been deprecated and will be removed in an upcoming release.

Gallery



Visual Studio project settings are transferred to the Nsight standalone tool



Key binding support for quick access



Enable/Disable tools to control visibility in Nsight menu

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