Tutorials and Samples

Discover Where Vectorization Pays Off The Most

Get Started Guide: Discover Where Vectorization Pays Off The Most

Sample: included in the product package

Learning Objective: Use Vectorization report to:

• Identify loops that will benefit most from vectorization.

• Identify what is blocking effective vectorization.

• Increase the confidence that vectorization is safe.

• Explore the benefit of alternative data reorganizations.

Prototype Threading Designs

Get Started Guide: Prototype Threading Designs

Sample: included in the product package

Learning Objective: Demonstrates an end-to-end workflow you can ultimately apply to your own applications:

1. Survey the target executable to locate the loops and functions where your application spends the most time.

2. In the target sources, add Intel Advisor annotations to mark possible parallel tasks and their enclosing parallel sites.

3. Check Suitability to predict the maximum parallel performance speedup of the target based on these annotations.

4. Check Dependencies to predict parallel data sharing problems in the target based on these annotations.

5. If the predicted maximum speedup benefit is worth the effort to fix the predicted parallel data sharing problems, fix the problems.

6. Recheck Suitability to see how your fixes impact the predicted maximum speedup.

7. If the predicted maximum speedup benefit is still worth the effort to add parallelism to the target, replace the annotations with parallel framework code that enables parallel execution.

Use the Automated Roofline Chart to Make Optimization Decisions - C++ Sample

Windows* OS Tutorial: HTML

Sample: Download roofline_demo_samples sample. You can download source code or pre-collected results to save time.

Duration: 20 minutes (with pre-collected results)

Learning Objective: Use the Roofline chart to answer the following questions:

• What is the maximum achievable performance with your current hardware resources?

• Does your application work optimally on current hardware resources?

• If not, what are the best candidates for optimization?

• Is memory bandwidth or compute capacity limiting performance for each optimization candidate?