并行示例

现象

多物理内核的情况下（128个），但并行线程只有1个，程序运行时长较久。

调优思路

通过最基本的OpenMP编程方式实现并行计算；因为在多核环境场景下，提升并行度是最直接的优化手段。

操作步骤

图1 并行示例代码

1. 运行矩阵行列大小为2048的parallel_matmult示例。

   1	./matmul 2048 1

   返回信息如下：

   1 2 3

   Size is 2048, Matrix multiplication method is: 1, Check correctness is: 0 Initialization time = 0.175117s Matrix multiplication time = 2.971563s

   矩阵行列大小为2048情况下，并行计算耗时3秒左右。

2. 创建矩阵行列大小为2048的parallel_matmult示例的roofline任务。

   1	devkit tuner roofline -o parallel_matmult_2048 -m region ./matmul 2048 1

   返回信息如下：

   1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

   Note: 1. Roofline task is currently only supported on the 920 platform. 2. The application must be a binary file in ELF format, and read permissions are required to detect the format of the application. 3. Roofline task collection needs to ensure the application has finished running. 4. The estimated time of roofline collection is about 3 * application estimated time. 5. Roofline analysis is available only on physical machines. 6. You can learn about the roofline profiling method by looking at document /usr/local/devkit/tuner/docs/ROOFLINE_KNOW_HOW.MD RFCOLLECT: Start collection for ./matmul RFCOLLECT: Launch application to collect performance metrics of ./matmul Size is 2048, Matrix multiplication method is: 1, Check correctness is: 0 Initialization time = 0.174164s ROOFLINE_EVENTS are initialized. Matrix multiplication time = 2.996051s RFCOLLECT: Launch application to do binary instrumentation of ./matmul Size is 2048, Matrix multiplication method is: 1, Check correctness is: 0 Initialization time = 0.523171s Matrix multiplication time = 3.427321s RFCOLLECT: Launch benchmarks for measuring roofs RFCOLLECT: Processing all collected data RFCOLLECT: Result is captured at /matrix_multiplication/rfcollect-20240506-154009.json RFCOLLECT: Run "rfreport /matrix_multiplication/rfcollect-20240506-154009.json" to get report. Get roofline report ... The roofline json report: /matrix_multiplication/parallel_matmult_2048.json The roofline html report: /matrix_multiplication/parallel_matmult_2048.html

3. 查看parallel_matmult_2048_html报告。
   图2 parallel_matmult_2048_html报告
   

   此时获取的roofs的并行度为128，获取到Elapsed Time 2.953s, GFLOP Count 17.18，Performance 5.818 GFLOPS。

优化效果

在多核环境场景下，提升并行度是最直接的优化手段。

图3 对比分析

Web模式的Roofline分析任务支持对比任务，可以使用Web模式查看对比分析结果。