安装
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2
| $ which nvprof
/usr/local/cuda/bin/nvprof
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基本使用
摘要模式
命令行直接运行
跟踪API
1
| nvprof --print-gpu-trace ./myApp
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保存在log里
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| sudo /usr/local/cuda/bin/nvprof --log-file a.log --metrics achieved_occupancy /staff/shaojiemike/github/cutests/22-commonstencil/common
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可视化
- nsight可以直接在远程机器上运行
- ssh -X host
- .ssh/config
- add
- XAuthLocation /opt/X11/bin/xauth #for macbookAir
- ForwardX11Trusted yes
- ForwardX11 yes
- Visual Profiler也可以ssh直接连接远程机器
- 或者导出分析结果以便可视化, 在Visual Profiler使用
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2
| nvprof --export-profile timeline.prof <app> <app args>
nvprof --analysis-metrics -o nbody-analysis.nvprof ./myApp
|
profile kernel
1
| sudo /usr/local/cuda/bin/ncu -k stencil_kernel -s 0 -c 1 /staff/shaojiemike/github/cutests/22-commonstencil/best
|
ncu-ui是可视化界面，但是没弄懂
带宽profile
上限测量
1
| # shaojiemike @ snode0 in ~/github/cuda-samples-11.0 [16:02:08] $ ./bin/x86_64/linux/release/bandwidthTest [CUDA Bandwidth Test] - Starting... Running on... Device 0: Tesla P40 Quick Mode Host to Device Bandwidth, 1 Device(s) PINNED Memory Transfers Transfer Size (Bytes) Bandwidth(GB/s) 32000000 11.8 Device to Host Bandwidth, 1 Device(s) PINNED Memory Transfers Transfer Size (Bytes) Bandwidth(GB/s) 32000000 13.0 Device to Device Bandwidth, 1 Device(s) PINNED Memory Transfers Transfer Size (Bytes) Bandwidth(GB/s) 32000000 244.3 Result = PASS NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled. # shaojiemike @ snode0 in ~/github/cuda-samples-11.0 [16:03:24] $ ./bin/x86_64/linux/release/p2pBandwidthLatencyTest
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实际值
nvprof通过指定与dram，L1或者L2 的metrics来实现。具体解释可以参考官网
在 Maxwell 和之后的架构中 L1 和 SMEM 合并
| Metric Name |
解释 |
| achieved_occupancy |
活跃cycle是 Warps 活跃的比例 |
| dram_read_throughput |
|
| dram_utilization |
在0到10的范围内，相对于峰值利用率，设备内存的利用率水平 |
| shared_load_throughput |
|
| shared_utilization |
|
| l2_utilization |
|
需要进一步的研究学习
暂无
遇到的问题
暂无
开题缘由、总结、反思、吐槽~~
参考文献
无