How Intel® AVX2 Improves Performance on Server Applications

The latest Intel® Xeon® processor E5 v3 family includes a feature called Intel® Advanced Vector Extensions 2 (Intel® AVX2), which can potentially improve application performance related to high performance computing, databases, and video processing. Here we will explain the context, and provide an example of how using Intel® AVX2 improved performance for a commonly known benchmark.

For existing vectorized code that uses floating point operations, you can gain a potential performance boost when running on newer platforms such as the Intel® Xeon® processor E5 v3 family by doing one of the following:

1. Recompile your code, using the Intel® compiler with the proper AVX2 switch to convert existing SSE code. See the Intel® Compiler Options for Intel® SSE and Intel® AVX generation (SSE2, SSE3, SSSE3, ATOM_SSSE3, SSE4.1, SSE4.2, ATOM_SSE4.2, AVX, AVX2) and processor-specific optimizations for more details.
2. Modify your code's function calls to leverage the Intel® Math Kernel Libraries (Intel® MKL) which are already optimized to use AVX2 where supported
3. Use the AVX2 intrinsic instructions. For high level language (such as C or C++) developers, you can use Intel® Intrinsic instructions to make the call and recompile code. See the Intel® Intrinsic Guide and Intel® 64 and IA-32 Architectures Optimization Reference Manual for more details
4. Code in assembly instructions directly. For low level language (such as assembly) developers, you can use those equivalent AVX2 instructions from their existing SSE code. See the Intel® 64 and IA-32 Architectures Optimization Reference Manual for more details

In this article, I will share a simple experiment using the Intel® Optimized LINPACK benchmark to demonstrate the performance gain of three different sized workloads (30K, 40K, and 75K) from Intel AVX2 running on Windows* and Linux* operating systems. I will also share the list of AVX2 instructions that were executed and the equivalent SSE instructions for developers who are interested in direct coding.

I used the following platform for the experiment:

Procedure for running LINPACK:

1. Download and install the following:
   1. Intel® Math Kernel Library – LINPACK Download
      http://software.intel.com/en-us/articles/intel-math-kernel-library-linpack-download
   2. Intel® Math Kernel Library (Intel® MKL)
      http://software.intel.com/en-us/intel-math-kernel-library-evaluation-options
2. Create input files for 30K, 75K, 100K from the “...\linpack” directory
3. For optimal performance, make the following Operating System and BIOS setting changes before running LINPACK:
   1. Turn off hyper-threading in the bios
   2. For Windows, set “MKL_CBWR=AVX2” on the command line and update the runme_xeon64.bat file to use the input files you previously created. For Linux, export the “MKL_CBWR=AVX2” setting on the command line and update the runme_xeon64 shell script file to use the input files you created.
   3. The results will be in Glops similar to Table 2
4. For Intel AVX runs, you will need to set the “MKL_CBWR=AVX” and repeat above steps.
5. For Intel SSE runs, you will need to set the “MKL_CBWR=SSE4_2” and repeat above steps.

What are the equivalent instructions for Intel AVX2, AVX, and SSE that were executed?

Table 1 has a list of equivalent instructions for Intel AVX2, AVX and SSE (SSE/SSE2/SSE3/SSE4). If you are thinking of moving your existing code to Intel AVX2.

Table 1– Intel AVX2, AVX, and Intel SSE Equivalent Instructions

The list in Table 1 is just a subset. The full list can be obtained from the Intel® 64 and IA-32 Architectures Optimization Reference Manual. Intel AVX2 and Intel AVX are complementing each other’s, the instructions will be shared to provide the necessary functionality.

What is the performance gain from running the LINPACK benchmark with Intel AVX2 vs. Intel SSE enabled and Intel AVX2 vs. Intel AVX on the Intel Xeon E5-2699 v3 processor-based server?

Table 2 shows the results from the three different workloads running on Windows* and Linux*. In the “Ratio Intel AVX2 vs. Intel SSE” column, the numbers show that the LINPACK benchmark produces ~2.2x-2.8x better performance when running with the combination of an Intel AVX2 optimized LINPACK and an Intel AVX2 capable processor. For the Intel AVX2 vs. Intel AVX column, the numbers show that the LINPACK benchmark produces ~1.3x-1.6x better performance. This is just an example of the potential performance boost for LINPACK. For other applications, the performance gain will vary depending on the optimized code and the hardware environment.

Table 2 – Results and Performance Gain from the LINPACK benchmark running on Intel® Xeon E5-2699 v3 two sockets server

With new AVX2 instructions and the 256 bit registers on Intel E5 processor family, LINPACK was able to take advantage of the new instructions to achieve over 2x performance in comparison to running LINPACK with SSE instructions and over 1.3x performance against LINPACK running with AVX instructions.

Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark* and MobileMark*, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products.

Configurations: Intel® Xeon® processor E5-2699 v3 @ 2.30GHz, 45MB L3 cache, 18 core pre-production system. Intel SSD S3500 Series (SSDSC2BB240G401) + Intel® SSD DC P3700 Series @ 400GB, 128GB memory (8x16GB DDR4 -2133Mhz), BIOS by Intel Corporation Version: SE5C610.86B.01.01.556.061320140714 BMC 0.20.6013 ME 03.00.05.402 SDR 0.10, Power supply: 1x 1100W Removable S-1100ADU00-201, running Microsoft* Windows Server 2012 R2 / SLES 11 SP3 Linux*

For more information go to http://www.intel.com/performance

Conclusion

From our LINPACK experiment, we see compelling performance benefits when going to an AVX2-enabled Intel® Xeon® processor; in this specific case, we saw a performance increase of ~2.2x-2.8x for AVX2 vs. SSE and ~1.3x-1.6x for AVX2 vs. AVX in our test environment, which is a strong case for developers who have SSE-enabled code and are weighing the benefit of moving to a newer Intel® Xeon® processor-based system with AVX2. The reference materials below can help developers learn how to migrate existing SSE code to Intel AVX2 code.

References

• How Intel® AVX Improves Performance on Server Application
• https://software.intel.com/en-us/articles/performance-tools-for-software-developers-intel-compiler-options-for-sse-generation-and-processor-specific-optimizations">Intel® Compiler Options for Intel® SSE and Intel® AVX generation (SSE2, SSE3, SSSE3, ATOM_SSSE3, SSE4.1, SSE4.2, ATOM_SSE4.2, AVX, AVX2) and processor-specific optimizations
• Intel® System Studio: Intel® AVX2 Support in the Intel® C++ Compiler
• Intel® AVX2 optimization in Intel® MKL
• Intel IPP support for Intel® AVX2
• Processing Arrays of Bits with Intel® Advanced Vector Extensions 2 (Intel® AVX2
• High Performance Multi-core Networked and Storage Systems for Linux
• Optimized Pseudo Random Number Generators with AVX2

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