View Results in CLI

Description of a
baseline
device where application performance was measured and a target device for which the application performance was modeled
Executive binary name
Top metrics for measured and estimated (accelerated) application performance
Top regions recommended for offloading to the target and performance metrics per region

Info: Selected accelerator to analyze: Intel(R) Gen11 Integrated Graphics Accelerator 64EU.
Info: Baseline Host: Intel(R) Core(TM) i7-9700K CPU @ 3.60GHz, GPU: Intel (R) .
Info: Binary Name: 'CFD'.
Info: An unknown atomic access pattern is specified: partial_sums_16. Possible values are same, sequential. sequential will be used.

Measured CPU Time: 44.858s    Accelerated CPU+GPU Time: 16.265s
Speedup for Accelerated Code: 3.5x    Number of Offloads: 7    Fraction of Accelerated Code: 60%

Top Offloaded Regions
---------------------------------------------------------------------------------------------------------------------------------
 Location                                               | CPU      | GPU      | Estimated Speedup | Bounded By | Data Transferred
---------------------------------------------------------------------------------------------------------------------------------
 [loop in compute_flux_ser at euler3d_cpu_ser.cpp:226]  |  36.576s |   9.340s |             3.92x | L3_BW      |         12.091MB
 [loop in compute_step_factor_ser at euler3d_cpu_ser....|   0.844s |   0.101s |             8.37x | LLC_BW     |          4.682MB
 [loop in time_step_ser at euler3d_cpu_ser.cpp:361]     |   0.516s |   0.278s |             1.86x | L3_BW      |         10.506MB
 [loop in time_step_ser at euler3d_cpu_ser.cpp:361]     |   0.456s |   0.278s |             1.64x | L3_BW      |         10.506MB
 [loop in time_step_ser at euler3d_cpu_ser.cpp:361]     |   0.432s |   0.278s |             1.55x | L3_BW      |         10.506MB
---------------------------------------------------------------------------------------------------------------------------------

View Results in GUI

Main metrics for the modeled performance of your program that indicates if you should offload your application to a target device.
Specific factors that prevent your code from achieving a better performance if executed on a target device in the Offload Bounded by.
Top five offloaded loops/functions that provide the highest benefit and top five not offloaded loops/functions with the reason why they were not offloaded.

View an Interactive HTML Report

Interactive HTML report that represents results in the similar way as GUI and enables you to view key estimated metrics for your application:
advisor-report.html
Collect GPU Roofline data to view results for
Offload Modeling
and
GPU Roofline Insights
perspectives in a single interactive HTML report.
Legacy HTML report that enables you to get the detailed information about functions in a call tree, download a configuration file for a target accelerator, and view perspective execution logs:
report.html
.

Save a Read-only Result Snapshot

A snapshot is a read-only copy of a project result, which you can view at any time using the

Intel Advisor

GUI. You can save a snapshot for a project using Intel Advisor GUI or CLI.

To save an active project result as a read-only snapshot from GUI: Click the button in the top ribbon of the report. In the

Create a Result Snapshot

dialog box, enter the snapshot details and save it.

To save an active project result as a read-only snapshot from CLI:

advisor --snapshot --project-dir=

<project-dir>

[--cache-sources] [--cache-binaries] --

<snapshot-path>

where:

--cache-sources
is an option to add application source code to the snapshot.
--cache-binaries
is an option to add application binaries to the snapshot.
<snapshot-path
is a path and a name for the snapshot. For example, if you specify
/tmp/new_snapshot
, a snapshot is saved in a
tmp
directory as
new_snapshot.advixeexpz
. You can skip this and save the snapshot to a current directory as
snapshot
XXX
.advixeexpz
.

To open the result snapshot in the

Intel Advisor

GUI, you can run the following command:

advisor-gui

<snapshot-path>

You can visually compare the saved snapshot against the current active result or other snapshot results.

See Create a Read-only Result Snapshot for details.

Result Interpretation

Examine regions recommended for offloading and view estimated performance of your application after offloading to a target platform assuming it is mostly bounded by compute limitations. You need to run at least the Survey, Trip Counts and FLOP (Characterization), and Performance Modeling analyses (
Low
accuracy) to collect this data.
Examine data transfers estimated for modeled regions and view estimated performance with data transfer estimations between host and target platforms for all memory levels and total data for loop/function. You need to run at least the Survey, Trip Counts and FLOP with callstacks, light data transfer simulation, and cache simulation (Characterization), and Performance Modeling analyses (
Medium
accuracy) to collect this data.
Check for dependencies issues and view a more accurate performance estimated considering loop/function dependencies. You need to run at least the Survey, Trip Counts and FLOP with callstacks, cache simulation, and medium data transfer simulation (Characterization), Dependencies, and Performance Modeling analyses (
High
accuracy) to collect this data.
Explore performance gain from GPU-to-GPU modeling to see how your DPC++, OpenMP* target, or OpenCL™ application can have a better performance if you run it on a different graphics processing unit (GPU) device.
Investigate non-offloaded code regions and understand why they are not profitable to run on a target platform. The higher accuracy level you run, the more accurate offload recommendations and non-offloaded reasons are.