An Introduction to GCC Compiler Intrinsics in Vector Processing
Finally, here are some performance tips.
First, get a recent compiler and use the best code generation options. (Check the info pages that come with your compiler for things like the -mcpu option.)
Second, profile your code. Humans are bad at guessing where the bottlenecks are. Fix the bottlenecks, not other parts.
Third, get the most work you can from each vector operation by using the vector with the narrowest type elements that your data will fit into. Get the most work you can in each time slice by having enough work that you keep your vector hardware busy. Take big bites of data. If your vector hardware can handle a lot of vectors at the same time, use them. However, exceeding the number of vector registers you have available will slow things down. (Check your processor's documentation.)
Fourth, don't re-invent the wheel. Intel, Freescale and ARM all offer libraries and code samples to help you get the most from their processors. These include Intel's Integrated Performance Primitives, Freescale's libmotovec and ARM's OpenMAX.
In summary, GCC offers intrinsics that allow you to get more from your processor without the work of going all the way to assembly. We have covered basic types and some of the vector math functions. When you use intrinsics, make sure you test thoroughly. Test for speed and correctness against a scalar version of your code. Different features of each processor and how well they operate means that this is a wide open field. The more effort you put into it, the more you will get out.
The GCC include files that map intrinsics to compiler built-ins (eg arm_neon.h) and the GCC info pages that explain those built-ins:http://gcc.gnu.org/onlinedocs/gcc/Target-Builtins.html
Integrated Performance Primitives
Freescale AltiVec Libs for Linux
AltiVec TM Technology Programming Interface Manual
Ian Ollmann's Altivec Tutorial
RealView Compilation Tools Compiler Reference Guide (especially Appendix E)
RealView Compilation Tools Assembler Guide (esp chapter 5)
Intel C++ Intrinsics Reference
Getting Started with DevOps - Including New Data on IT Performance from Puppet Labs 2015 State of DevOps Report
August 27, 2015
12:00 PM CDT
DevOps represents a profound change from the way most IT departments have traditionally worked: from siloed teams and high-anxiety releases to everyone collaborating on uneventful and more frequent releases of higher-quality code. It doesn't matter how large or small an organization is, or even whether it's historically slow moving or risk averse — there are ways to adopt DevOps sanely, and get measurable results in just weeks.
Free to Linux Journal readers.Register Now!
- Hacking a Safe with Bash
- Django Models and Migrations
- Secure Server Deployments in Hostile Territory, Part II
- The Controversy Behind Canonical's Intellectual Property Policy
- Huge Package Overhaul for Debian and Ubuntu
- Home Automation with Raspberry Pi
- Shashlik - a Tasty New Android Simulator
- Embed Linux in Monitoring and Control Systems
- KDE Reveals Plasma Mobile
- diff -u: What's New in Kernel Development