CUDA Profiler：计算内存并计算利用率

我正在尝试使用ubuntu上的CUDA nsight profiler对内存带宽利用率和GPU加速应用程序的吞吐量利用率建立两个总体衡量指标。该应用程序在Tesla K20c GPU上运行。

我想要的两个度量在某种程度上可以与该图给出的度量进行比较：

问题在于这里没有给出确切的数字，更重要的是我不知道这些百分比是如何计算的。

内存带宽利用率

探查器告诉我，我的GPU的最大全局内存带宽为208 GB / s。

这是指设备内存带宽还是全局内存带宽？它说全球，但第一个对我来说更有意义。

For my kernel the profiler tells me that the Device Memory Bandwidth is 98.069 GB/s.

Assuming that the max of 208 GB/s refer to the Device Memory could I then simply calculate the Memory BW Utilization as 90.069/208 = 43%? Note that this kernel is executed multiple times without additional CPU-GPU data transfers. The system BW is therefore not important.

Compute Throughput Utilization

I am not exactly sure what the best way is to put Compute Throughput Utilization into a number. My best guess is to use the Instructions per Cycle to max Instructions per cycle ratio. The profiler tells me that the max IPC is 7 (see picture above).

First of all, what does that actually mean? Each multiprocessor has 192 cores and therefore a maximum of 6 active warps. Wouldnt that mean that max IPC should be 6?

The profiler tells me that my kernel has issued IPC = 1.144 and executed IPC = 0.907. Should I calculate the compute utilization as 1.144/7 = 16% or 0.907/7 = 13% or none of these?

Are these two measurements (Memory and compute utilization) giving an adequate first impression of how efficiently my kernel is using the resources? Or are there other important metrics that should be included?

Additional Graph