User Guide

Contents

What's New in
Intel® Advisor

This topic lists new high-level features and improvements in
Intel® Advisor
. For a full list of new features, see
Intel Advisor
Release Notes
.

Intel® Advisor
2023.0

GPU Profiling and Roofline on PVC-XT:
Get actionable advice to design code that runs optimally on Intel® Data Center GPU MAX Series (formerly code named Ponte Vecchio).
Discover GPU application performance characterization, such as bandwidth sensitivity, instruction mix, and cache-line use.
Automated Roofline Analysis helps to identify and prioritize memory, cache, or compute bottlenecks and understand their likely causes.

Intel® Advisor
2022.1

  • Usability
    :
    • Performance metrics in GPU Roofline Source view in the
      Intel Advisor
      GUI
      In the
      GPU Roofline Insights
      report, you can switch to
      Source View
      and examine the source code of your application with performance metrics for each kernel, such as elapsed time and memory traffic.
      Source view in the GPU Roofline Insights report now includes per-kernel performance metrics
    • New panes in an interactive HTML Report: GPU Details in the
      GPU Roofline Insights
      perspective and Data Transfer Estimations in the
      Offload Modeling
      perspective
      The interactive HTML report, which combines
      Offload Modeling
      and
      GPU Roofline Insights
      results, now includes two new panes, which are similar to the panes with the same name in the
      Intel Advisor
      GUI report:
      • GPU Roofline Insights
        perspective includes the
        GPU Details
        pane, which reports detailed code analytics for a selected kernel, such as Roofline guidance with the main limiting roof and estimated speedup after optimization, compute and memory bandwidth, memory usage metrics.
        GPU Roofline Insights interactive HTML report now includes GPU Details pane
      • Offload Modeling
        perspective includes the
        Data Transfer Estimations
        pane, which reports estimated data transferred between host and target devices in each direction and a list of offloaded objects.
        Offload Modleing interactive HTML report now includes Data Transfer pane
      You can use the interactive HTML reports to analyze
      Intel Advisor
      results on a remote machine using your web browser or share the results. See Work with Standalone HTML Reports for details.
  • Offload Modeling
    :
    • Adjustable hardware parameters in an interactive HTML report and GUI report
      Offload Modeling
      report includes a new
      Modeling Parameters
      pane, which shows available target devices for modeling and hardware configuration parameters for a selected device. Each parameter is a slider that you can adjust to a desired value to get a custom configuration for remodeling.
      Offload Modeling report now includes a Modeling Parameters pane with interactive sliders for each hardware parameter
      The pane is available in the interactive HTML report and
      Intel Advisor
      GUI report and has the same functionality. You can use it to:
      • Examine device parameters that the application performance was modeled on to understand how they affect the estimated performance.
      • Change the target device to compare the new configuration with the current modeled device.
      • Adjust the parameters and remodel performance for a custom device. You can experiment with parameters to see how they affect the application performance or adjust the configuration to model performance for a future or a specific device not listed in the target devices. See the sections below for a full workflow.
        For CPU-to-GPU modeling, you can remodel performance using
        Intel Advisor
        CLI only.
      See Model Application Performance on a Custom Target GPU Device for more information about how to work with the pane.
    • New recommendation to optimize data transfer costs with data reuse when porting your application from a CPU to a GPU
      Offload Modeling
      perspective introduces a new actionable recommendation for optimizing data transfer costs with data reuse before porting your application from a CPU to a GPU. Data reuse can help you improve the application performance on the GPU by optimizing data transfer efficiency.
      The recommendation is reported in a Recommendations pane of the Accelerated Regions tab. The recommendation includes estimated performance characteristics and data reuse gain, as well as code snippet examples for applying data reuse techniques.
      Data reuse recommendaction can help you to optimize data transfer efficiency and improve performance
  • Documentation
    :

Intel® Advisor
2022.0

  • GPU Roofline:
    • New recommendation to optimize GPU general purpose register file (GRF) usage and improve performance
      .
      The
      GPU Roofline Insights
      perspective introduces actionable recommendations for improving your application performance on GPU by optimizing GRF usage. The recommendations are reported in a
      Recommendations
      pane in the
      GPU Roofline Regions
      report. See Get Recommendations for details.
    • New GPU memory and compute metrics
      .
      The
      GPU
      pane in the
      GPU Roofline Regions
      tab introduces several new metrics. Some of the new metrics are:
      Memory metrics:
      Compute metrics:
  • Documentation:
    • Command-line cheat sheet for quick reference
      Introduced a new downloadable
      Intel Advisor
      command-line cheat sheet
      , which lists the most useful command-line interface (CLI) options. You can use this print-friendly PDF for quick reference on the
      Intel Advisor
      CLI.
Support for Microsoft* Visual Studio* 2017 is deprecated as of the Intel® oneAPI 2022.1 release, and will be removed in a future release.

Product and Performance Information

1

Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.