Intel® Advisor 2021.1
- Data Parallel C++ (DPC++):
- Implemented support for Data Parallel C++ (DPC++) code performance profiling on CPU and GPU targets.
- Implemented support for oneAPI Level Zero specification for DPC++ applications.
- Introduced a new and improvedIntel Advisoruser interface (UI) that includes:
To switch back to the old UI, set theADVISOR_EXPERIMANTAL=advixe_gui.
- New look-and-feel for multiple tabs and panes, for example,Workflowpane andToolbars
- Offload ModelingandGPU Rooflineworkflows integrated in GUI
- New notion ofperspective, which is a complete analysis workflow that you can customize to manage accuracy and overhead trade-off. Each perspective collects performance data, but processes and presents it differently so that you could look at it from different points of view depending on your goal.Intel AdvisorincludesOffload Modeling,GPU Roofline Insights,Vectorization and Code Insights,CPU / Memory Roofline Insights, andThreadingperspectives.
- Renamed executables and environment scripts:
See the Command Line Interface for details and sample command lines.The previous command line interface and executables are supported for backward compatibility.
- advixe-clis renamed toadvisor.
- advixe-guiis renamed toadvisor-gui.
- advixe-pythonis renamed toadvisor-python.
- advixe-vars.[c]shandadvixe-vars.batare renamed toadvisor-vars.[c]shandadvisor-vars.batrespectively.
- Offload Modeling:
- Introduced the Offload Modeling perspective (previously known as Offload Advisor) that you can use to prepare your code for efficient GPU offload even before you have a hardware. Identify parts of code can be efficiently offloaded to a target device, estimate potential speedup, and locate bottlenecks.
- Introduced data transfer analysis as an addition to the Offload Modeling perspective. The analysis reportsdata transfer costsestimated for offloading to a target device, estimatedamount of memoryyour application uses per memory level, andhintsfor data transfer optimizations.
- Introduced strategies to manage kernel invocation taxes (or kernel launch taxes) when modeling performance: do not hide invocation taxes, hide all invocation taxes except the first one, hide a part of invocation taxes. For more information, see Manage Invocation Taxes.
- Added support for modeling application performance for the Intel® Iris® Xe MAX graphics.
- Introduced Memory-Level Roofline feature (previously known as Integrated Roofline, tech preview feature). Memory-Level Roofline collects metrics for all memory levels and allows you to identify memory bottlenecks at different cache levels (L1, L2, L3 or DRAM).
- Added a limiting memory level roof to the Roofline guidance and recommendations, which improves recommendation accuracy.
- Added a single-kernel Roofline guidance for all memory levels with dots for multiple levels of a memory subsystem and limiting roof highlighting to theCode Analyticspane.
- Introduced a GPU Roofline Insights perspective. GPU Roofline visualizes actual performance of GPU kernels against hardware-imposed performance limitations. Use it to identify the main limiting factor of your application performance and get recommendations for effective memory vs. compute optimization. GPU Roofline report supports float and integer data types and reports metrics for all memory levels.
- Added support for profiling GPU workloads that run on the Intel® Iris® Xe MAX graphics and building GPU Roofline for them.
- Flow Graph Analyzer:
- Added rules to the Static Rule-check engine to determine issues with unnecessary copies during the creation of buffers, host pointer accessor usage in a loop, multiple build/compilations for the same kernel when invoked multiple times.
- Introduced a PDF version of theIntel AdvisorUser Guide. ClickDownload as PDFat the top of this page to use the PDF version.
- Introduced a new user guide structure that focuses on the new UI and reflects the usage flow to improve usability.