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项目作者： ekondis

项目描述 ：
用于评估混合操作强度内核（CUDA，OpenCL，HIP）上的GPU的GPU基准测试工具
高级语言： C++
项目地址: git://github.com/ekondis/mixbench.git
创建时间： 2015-06-25T16:27:29Z
项目社区：https://github.com/ekondis/mixbench
开源协议：GNU General Public License v2.0
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mixbench

The purpose of this benchmark tool is to evaluate performance bounds of GPUs (or CPUs) on mixed operational intensity kernels. The executed kernel is customized on a range of different operational intensity values. Modern GPUs are able to hide memory latency by switching execution to threads able to perform compute operations. Using this tool one can assess the practical optimum balance in both types of operations for a compute device. CUDA, HIP, OpenCL and SYCL implementations have been developed, targeting GPUs, or OpenMP when using a CPU as a target.

Implementations

  • CUDA: mixbench-cuda
  • OpenCL: mixbench-opencl
  • HIP: mixbench-hip
  • SYCL: mixbench-sycl
  • CPU/OpenMP: mixbench-cpu

Since each implementation resides in a separate folder, please check the documentation available within each sub-project’s folder.

Kernel types

Four types of experiments are executed combined with global memory accesses:

  1. Single precision Flops (multiply-additions)
  2. Double precision Flops (multiply-additions)
  3. Half precision Flops (multiply-additions, for GPUs only)
  4. Integer multiply-addition operations

How to build

Building is based on CMake files.
Thus, to build a particular implementation use the proper CMakeLists.txt residing in each subdirectory,
e.g. for the OpenCL implementation you may use the commands as follows:

  1. mkdir build
  2. cd build
  3. cmake ../mixbench-opencl
  4. cmake --build ./

For more information, check available READMEs within each subfolder.

Execution results

A typical execution output on an NVidia RTX-2070 GPU is:

  1. mixbench/read-only (v0.03-2-gbccfd71)
  2. ------------------------ Device specifications ------------------------
  3. Device:              GeForce RTX 2070
  4. CUDA driver version: 10.20
  5. GPU clock rate:      1620 MHz
  6. Memory clock rate:   3500 MHz
  7. Memory bus width:    256 bits
  8. WarpSize:            32
  9. L2 cache size:       4096 KB
  10. Total global mem:    7979 MB
  11. ECC enabled:         No
  12. Compute Capability:  7.5
  13. Total SPs:           2304 (36 MPs x 64 SPs/MP)
  14. Compute throughput:  7464.96 GFlops (theoretical single precision FMAs)
  15. Memory bandwidth:    448.06 GB/sec
  16. -----------------------------------------------------------------------
  17. Total GPU memory 8366784512, free 7941521408
  18. Buffer size:          256MB
  19. Trade-off type:       compute with global memory (block strided)
  20. Elements per thread:  8
  21. Thread fusion degree: 4
  22. ----------------------------------------------------------------------------- CSV data -----------------------------------------------------------------------------
  23. Experiment ID, Single Precision ops,,,,              Double precision ops,,,,              Half precision ops,,,,                Integer operations,,, 
  24. Compute iters, Flops/byte, ex.time,  GFLOPS, GB/sec, Flops/byte, ex.time,  GFLOPS, GB/sec, Flops/byte, ex.time,  GFLOPS, GB/sec, Iops/byte, ex.time,   GIOPS, GB/sec
  25.             0,      0.250,    0.32,  104.42, 417.68,      0.125,    0.63,   53.04, 424.35,      0.500,    0.32,  211.41, 422.81,     0.250,    0.32,  105.58, 422.30
  26.             1,      0.750,    0.32,  316.34, 421.79,      0.375,    0.63,  158.69, 423.18,      1.500,    0.32,  634.22, 422.81,     0.750,    0.32,  317.30, 423.07
  27.             2,      1.250,    0.32,  528.46, 422.77,      0.625,    0.78,  215.91, 345.45,      2.500,    0.32, 1055.97, 422.39,     1.250,    0.32,  528.57, 422.86
  28.             3,      1.750,    0.32,  738.81, 422.17,      0.875,    1.08,  218.17, 249.34,      3.500,    0.32, 1478.95, 422.56,     1.750,    0.32,  740.59, 423.20
  29.             4,      2.250,    0.32,  951.33, 422.81,      1.125,    1.38,  219.57, 195.17,      4.500,    0.32, 1902.66, 422.81,     2.250,    0.32,  950.66, 422.51
  30.             5,      2.750,    0.32, 1162.74, 422.81,      1.375,    1.67,  220.38, 160.28,      5.500,    0.32, 2328.52, 423.37,     2.750,    0.32, 1162.74, 422.81
  31.             6,      3.250,    0.32, 1374.56, 422.94,      1.625,    1.97,  220.99, 135.99,      6.500,    0.32, 2756.62, 424.10,     3.250,    0.32, 1375.81, 423.32
  32.             7,      3.750,    0.32, 1592.45, 424.65,      1.875,    2.27,  221.38, 118.07,      7.500,    0.32, 3169.50, 422.60,     3.750,    0.32, 1585.55, 422.81
  33.             8,      4.250,    0.32, 1796.95, 422.81,      2.125,    2.57,  221.71, 104.33,      8.500,    0.32, 3587.76, 422.09,     4.250,    0.37, 1545.63, 363.68
  34.             9,      4.750,    0.32, 2006.34, 422.39,      2.375,    2.87,  221.85,  93.41,      9.500,    0.32, 3995.38, 420.57,     4.750,    0.32, 1998.29, 420.69
  35.            10,      5.250,    0.32, 2209.52, 420.86,      2.625,    3.17,  222.02,  84.58,     10.500,    0.32, 4439.54, 422.81,     5.250,    0.32, 2220.44, 422.94
  36.            11,      5.750,    0.32, 2434.12, 423.32,      2.875,    3.47,  222.17,  77.28,     11.500,    0.32, 4855.01, 422.17,     5.750,    0.32, 2426.77, 422.05
  37.            12,      6.250,    0.32, 2638.06, 422.09,      3.125,    3.78,  222.18,  71.10,     12.500,    0.32, 5227.20, 418.18,     6.250,    0.38, 2202.15, 352.34
  38.            13,      6.750,    0.32, 2841.95, 421.03,      3.375,    4.08,  222.30,  65.87,     13.500,    0.32, 5712.58, 423.15,     6.750,    0.32, 2850.54, 422.30
  39.            14,      7.250,    0.32, 3065.39, 422.81,      3.625,    4.37,  222.45,  61.36,     14.500,    0.32, 6135.74, 423.15,     7.250,    0.32, 3065.08, 422.77
  40.            15,      7.750,    0.33, 3143.40, 405.60,      3.875,    4.67,  222.57,  57.44,     15.500,    0.32, 6546.34, 422.34,     7.750,    0.32, 3268.89, 421.79
  41.            16,      8.250,    0.32, 3482.59, 422.13,      4.125,    4.98,  222.57,  53.96,     16.500,    0.32, 6957.48, 421.67,     8.250,    0.39, 2803.68, 339.84
  42.            17,      8.750,    0.32, 3693.66, 422.13,      4.375,    5.28,  222.53,  50.86,     17.500,    0.32, 7396.24, 422.64,     8.750,    0.32, 3694.77, 422.26
  43.            18,      9.250,    0.32, 3901.58, 421.79,      4.625,    5.58,  222.58,  48.12,     18.500,    0.32, 7786.72, 420.90,     9.250,    0.32, 3897.66, 421.37
  44.            20,     10.250,    0.32, 4312.53, 420.73,      5.125,    6.18,  222.66,  43.45,     20.500,    0.32, 8640.66, 421.50,    10.250,    0.41, 3374.54, 329.22
  45.            22,     11.250,    0.32, 4729.94, 420.44,      5.625,    6.78,  222.74,  39.60,     22.500,    0.32, 9452.31, 420.10,    11.250,    0.32, 4734.21, 420.82
  46.            24,     12.250,    0.32, 5148.83, 420.31,      6.125,    7.36,  223.51,  36.49,     24.500,    0.32,10346.40, 422.30,    12.250,    0.42, 3900.12, 318.38
  47.            28,     14.250,    0.32, 6009.94, 421.75,      7.125,    8.53,  224.23,  31.47,     28.500,    0.32,11975.32, 420.19,    14.250,    0.44, 4368.11, 306.53
  48.            32,     16.250,    0.32, 6795.36, 418.18,      8.125,    9.72,  224.31,  27.61,     32.500,    0.32,13605.64, 418.64,    16.250,    0.45, 4797.12, 295.21
  49.            40,     20.250,    0.34, 7899.43, 390.10,     10.125,   12.11,  224.50,  22.17,     40.500,    0.33,16371.37, 404.23,    20.250,    0.50, 5464.85, 269.87
  50.            48,     24.250,    0.41, 8029.04, 331.09,     12.125,   14.49,  224.58,  18.52,     48.500,    0.40,16468.89, 339.56,    24.250,    0.54, 5986.22, 246.85
  51.            56,     28.250,    0.47, 8114.58, 287.24,     14.125,   16.88,  224.65,  15.90,     56.500,    0.46,16443.12, 291.03,    28.250,    0.60, 6342.42, 224.51
  52.            64,     32.250,    0.53, 8154.47, 252.85,     16.125,   19.26,  224.72,  13.94,     64.500,    0.52,16536.22, 256.38,    32.250,    0.66, 6591.93, 204.40
  53.            80,     40.250,    0.66, 8242.80, 204.79,     20.125,   24.03,  224.79,  11.17,     80.500,    0.65,16644.88, 206.77,    40.250,    0.78, 6909.54, 171.67
  54.            96,     48.250,    0.78, 8321.35, 172.46,     24.125,   28.80,  224.85,   9.32,     96.500,    0.78,16685.23, 172.90,    48.250,    0.91, 7108.62, 147.33
  55.           128,     64.250,    1.03, 8337.22, 129.76,     32.125,   38.34,  224.91,   7.00,    128.500,    1.03,16775.65, 130.55,    64.250,    1.18, 7295.18, 113.54
  56.           192,     96.250,    1.54, 8414.49,  87.42,     48.125,   57.42,  224.97,   4.67,    192.500,    1.53,16847.93,  87.52,    96.250,    1.74, 7431.64,  77.21
  57.           256,    128.250,    2.06, 8362.01,  65.20,     64.125,   76.50,  225.02,   3.51,    256.500,    2.06,16693.65,  65.08,   128.250,    2.30, 7477.75,  58.31
  58. --------------------------------------------------------------------------------------------------------------------------------------------------------------------

And here is a chart illustrating the results extracted above:

RTX-2070 execution results

Publications

If you use this benchmark tool for a research work please provide citation to any of the following papers:

Elias Konstantinidis, Yiannis Cotronis,
“A quantitative roofline model for GPU kernel performance estimation using micro-benchmarks and hardware metric profiling”,
Journal of Parallel and Distributed Computing, Volume 107, September 2017, Pages 37-56, ISSN 0743-7315,
https://doi.org/10.1016/j.jpdc.2017.04.002.
URL: http://www.sciencedirect.com/science/article/pii/S0743731517301247

Konstantinidis, E., Cotronis, Y.,
“A Practical Performance Model for Compute and Memory Bound GPU Kernels”,
Parallel, Distributed and Network-Based Processing (PDP), 2015 23rd Euromicro International Conference on , vol., no., pp.651-658, 4-6 March 2015
doi: 10.1109/PDP.2015.51
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7092788&isnumber=7092002