apeforest opened a new issue #17239: Cmake with NCCL flag does not work.
URL: https://github.com/apache/incubator-mxnet/issues/17239
 
 
   ## Description
   If I build mxnet with NCCL using cmake, it failed with "Could not find NCCL 
libraries" even though my NCCL is installed at /usr/local/cuda/include
   ## Reproduce
   ```
   cmake -GNinja -DUSE_CUDA=ON -DCMAKE_CUDA_COMPILER_LAUNCHER=ccache 
-DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache 
-DCMAKE_BUILD_TYPE=Release -DUSE_CUDNN=ON -DUSE_NCCL=ON ..
   
   CMake Warning at CMakeLists.txt:299 (message):
     Could not find NCCL libraries
   ```
   ## Environment
   
   We recommend using our script for collecting the diagnositc information. Run 
the following command and paste the outputs below:
   ```
   curl --retry 10 -s 
https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py | 
python
   
   ----------Python Info----------
   Version      : 3.6.6
   Compiler     : GCC 7.2.0
   Build        : ('default', 'Jun 28 2018 17:14:51')
   Arch         : ('64bit', '')
   ------------Pip Info-----------
   Version      : 19.3.1
   Directory    : /home/ubuntu/anaconda3/lib/python3.6/site-packages/pip
   ----------MXNet Info-----------
   No MXNet installed.
   ----------System Info----------
   Platform     : Linux-4.4.0-1096-aws-x86_64-with-debian-stretch-sid
   system       : Linux
   node         : ip-172-31-20-50
   release      : 4.4.0-1096-aws
   version      : #107-Ubuntu SMP Thu Oct 3 01:51:58 UTC 2019
   ----------Hardware Info----------
   machine      : x86_64
   processor    : x86_64
   Architecture:          x86_64
   CPU op-mode(s):        32-bit, 64-bit
   Byte Order:            Little Endian
   CPU(s):                64
   On-line CPU(s) list:   0-63
   Thread(s) per core:    2
   Core(s) per socket:    16
   Socket(s):             2
   NUMA node(s):          2
   Vendor ID:             GenuineIntel
   CPU family:            6
   Model:                 79
   Model name:            Intel(R) Xeon(R) CPU E5-2686 v4 @ 2.30GHz
   Stepping:              1
   CPU MHz:               2699.984
   CPU max MHz:           3000.0000
   CPU min MHz:           1200.0000
   BogoMIPS:              4600.11
   Hypervisor vendor:     Xen
   Virtualization type:   full
   L1d cache:             32K
   L1i cache:             32K
   L2 cache:              256K
   L3 cache:              46080K
   NUMA node0 CPU(s):     0-15,32-47
   NUMA node1 CPU(s):     16-31,48-63
   Flags:                 fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge 
mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx pdpe1gb rdtscp lm 
constant_tsc arch_perfmon rep_good nopl xtopology nonstop_tsc aperfmperf pni 
pclmulqdq monitor est ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt 
tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 
3dnowprefetch invpcid_single kaiser fsgsbase bmi1 hle avx2 smep bmi2 erms 
invpcid rtm rdseed adx xsaveopt ida
   ----------Network Test----------
   Setting timeout: 10
   Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0060 
sec, LOAD: 0.5026 sec.
   Timing for GluonNLP GitHub: https://github.com/dmlc/gluon-nlp, DNS: 0.0011 
sec, LOAD: 0.5116 sec.
   Timing for GluonNLP: http://gluon-nlp.mxnet.io, DNS: 0.1051 sec, LOAD: 
0.3917 sec.
   Timing for D2L: http://d2l.ai, DNS: 0.0108 sec, LOAD: 0.2085 sec.
   Timing for D2L (zh-cn): http://zh.d2l.ai, DNS: 0.1761 sec, LOAD: 0.1178 sec.
   Timing for FashionMNIST: 
https://repo.mxnet.io/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, 
DNS: 0.1306 sec, LOAD: 0.1471 sec.
   Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0123 sec, LOAD: 
0.4014 sec.
   Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.0120 sec, 
LOAD: 0.0739 sec.
   ```
   

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