Difference between revisions of "SPO600 Vectorization Lab"
Chris Tyler (talk | contribs) |
Chris Tyler (talk | contribs) |
||
| Line 4: | Line 4: | ||
== Lab 5 == | == Lab 5 == | ||
| − | # Write a short program that creates two 1000-element integer arrays and fills them with random numbers, then sums those two arrays to a third array, and finally sums the third array | + | # Write a short program that creates two 1000-element integer arrays and fills them with random numbers in the range -1000 to +1000, then sums those two arrays element-by-element to a third array, and finally sums the third array and prints the result. |
# Compile this program on [[SPO600 Servers#AArch64: aarchie|aarchie]] in such a way that the code is auto-vectorized. | # Compile this program on [[SPO600 Servers#AArch64: aarchie|aarchie]] in such a way that the code is auto-vectorized. | ||
# Annotate the emitted code (i.e., obtain a dissassembly via <code>objdump -d</code> and add comments to the instructions in <code><main></code> explaining what the code does). | # Annotate the emitted code (i.e., obtain a dissassembly via <code>objdump -d</code> and add comments to the instructions in <code><main></code> explaining what the code does). | ||
Revision as of 22:39, 1 October 2017
Purpose of this Lab
This lab is designed to explore single instruction/multiple data (SIMD) vectorization, and the auto-vectorization capabilities of the GCC compiler.
This lab is designed to explore single instruction/multiple data (SIMD) vectorization, and the auto-vectorization capabilities of the GCC compiler.
Lab 5
- Write a short program that creates two 1000-element integer arrays and fills them with random numbers in the range -1000 to +1000, then sums those two arrays element-by-element to a third array, and finally sums the third array and prints the result.
- Compile this program on aarchie in such a way that the code is auto-vectorized.
- Annotate the emitted code (i.e., obtain a dissassembly via
objdump -dand add comments to the instructions in<main>explaining what the code does). - Write a blog post discussing your findings. Include:
- The source code
- The compiler command line used to build the code
- Your annotated dissassembly listing - Prove that the code is vectorized, for example, by pointing out the use of vector registers and SIMD instructions.
- Your reflections on the experience and the results
Resources
- Auto-Vectorization in GCC - Main project page for the GCC auto-vectorizer.
- Auto-vectorization with gcc 4.7 - An excellent discussion of the capabilities and limitations of the GCC auto-vectorizer, intrinsics for providing hints to GCC, and other code pattern changes that can improve results. Note that there has been some improvement in the auto-vectorizer since this article was written. This article is strongly recommended.
- Intel (Auto)Vectorization Tutorial - this deals with the Intel compiler (ICC) but the general technical discussion is valid for other compilers such as gcc and llvm
