Open vijayaramaraju-kalidindi opened 3 weeks ago
Looks like CUDA isn't functional; I'd run a simple CUDA test first and ensure it works before running the NCCL perf tests.
Looks like CUDA isn't functional; I'd run a simple CUDA test first and ensure it works before running the NCCL perf tests.
I have run dgcm diagnostics. It says unable to initialize the CUDA library. How do we correct it??
sh-5.1# /usr/bin/dcgmi diag --run 3 --fail-early
Successfully ran diagnostic for group.
+---------------------------+------------------------------------------------+
| Diagnostic | Result |
+===========================+================================================+
|----- Metadata ----------+------------------------------------------------|
| DCGM Version | 3.3.8 |
| Driver Version Detected | 560.35.03 |
| GPU Device IDs Detected | 2330,2330,2330,2330,2330,2330,2330,2330 |
|----- Deployment --------+------------------------------------------------|
| Denylist | Pass |
| NVML Library | Pass |
| CUDA Main Library | Pass |
| Permissions and OS Blocks | Pass |
| Persistence Mode | Pass |
| Info | Persistence mode for GPU 0 is disabled. Enabl |
| | e persistence mode by running "nvidia-smi -i |
| |
Mentioned issue was resolved post enabling fabric manger service. We have then ran NCCL tests with in the server successfully.
NCCL tests across the server still gives an issue.
We are using below command to run NCCL tests across 2 hosts, but command is not yielding any output. Even environment variables like NCC_DEBUG=INFO are not working as they are not giving any info output while running the command.
/usr/lib64/openmpi/bin/mpirun -x NCCL_DEBUG=INFO --bind-to numa -np 16 -H jm01gp1jiobrain02:8,jm01gp1jiobrain03:8 ./build/all_reduce_perf -b8 -e16G -f2 --mca btl tcp,self --mca btl_tcp_if_include bond0.1239
Note: NCCL tests are being run on baremetal hosts which has 8 H100 GPU per host with RHEL 9.4 OS.
I would expect the command line to look more like this
/usr/lib64/openmpi/bin/mpirun -x NCCL_DEBUG=INFO --bind-to numa -np 16 -H jm01gp1jiobrain02:8,jm01gp1jiobrain03:8 \
--mca btl tcp,self --mca btl_tcp_if_include bond0.1239 ./build/all_reduce_perf -b8 -e16G -f2
Can you also try compiling & running a simple MPI program such as:
https://raw.githubusercontent.com/pmodels/mpich/main/examples/cpi.c
on 16 processes across both nodes.
I would expect the command line to look more like this
/usr/lib64/openmpi/bin/mpirun -x NCCL_DEBUG=INFO --bind-to numa -np 16 -H jm01gp1jiobrain02:8,jm01gp1jiobrain03:8 \ --mca btl tcp,self --mca btl_tcp_if_include bond0.1239 ./build/all_reduce_perf -b8 -e16G -f2
Can you also try compiling & running a simple MPI program such as:
https://raw.githubusercontent.com/pmodels/mpich/main/examples/cpi.c
on 16 processes across both nodes.
Hi,
Tried but didn't work. Got to know that command was not yielding output as host from where mpirun command is being ran is unable to autossh the target node. Post enabling auto ssh things worked.
My case was caused by nvidia-fabricmanager
fault.
Messages of nvidia-fabricmanager service is expressive enough to to figure out what wrong. After makes nvidia-fabricmanager happy, cuda work as expected.
We have a server with 8 H100 GPU with cuda version 12.6 and nccl version 2.23.4.
When we are running nccl test as per the command provided in - https://github.com/nvidia/nccl-tests we are facing below issue.
[root@test nccl-tests-master]# ./build/all_reduce_perf -b 8 -e 128M -f 2 -g 8
nThread 1 nGpus 8 minBytes 8 maxBytes 134217728 step: 2(factor) warmup iters: 5 iters: 20 agg iters: 1 validation: 1 graph: 0
#
Using devices
test: Test CUDA failure common.cu:941 'system not yet initialized' .. test pid 54340: Test failure common.cu:891
##################################################################
More info from nvidia-smi
[root@test nccl-tests-master]# nvidia-smi Fri Nov 8 02:11:26 2024 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 560.35.03 Driver Version: 560.35.03 CUDA Version: 12.6 | |-----------------------------------------+------------------------+----------------------+ | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA H100 80GB HBM3 Off | 00000000:19:00.0 Off | 0 | | N/A 38C P0 70W / 700W | 1MiB / 81559MiB | 0% Default | | | | Disabled | +-----------------------------------------+------------------------+----------------------+ | 1 NVIDIA H100 80GB HBM3 Off | 00000000:3B:00.0 Off | 0 | | N/A 35C P0 73W / 700W | 1MiB / 81559MiB | 0% Default | | | | Disabled | +-----------------------------------------+------------------------+----------------------+ | 2 NVIDIA H100 80GB HBM3 Off | 00000000:4C:00.0 Off | 0 | | N/A 32C P0 71W / 700W | 1MiB / 81559MiB | 0% Default | | | | Disabled | +-----------------------------------------+------------------------+----------------------+ | 3 NVIDIA H100 80GB HBM3 Off | 00000000:5D:00.0 Off | 0 | | N/A 35C P0 73W / 700W | 1MiB / 81559MiB | 0% Default | | | | Disabled | +-----------------------------------------+------------------------+----------------------+ | 4 NVIDIA H100 80GB HBM3 Off | 00000000:9B:00.0 Off | 0 | | N/A 38C P0 73W / 700W | 1MiB / 81559MiB | 0% Default | | | | Disabled | +-----------------------------------------+------------------------+----------------------+ | 5 NVIDIA H100 80GB HBM3 Off | 00000000:BB:00.0 Off | 0 | | N/A 35C P0 70W / 700W | 1MiB / 81559MiB | 0% Default | | | | Disabled | +-----------------------------------------+------------------------+----------------------+ | 6 NVIDIA H100 80GB HBM3 Off | 00000000:CB:00.0 Off | 0 | | N/A 37C P0 72W / 700W | 1MiB / 81559MiB | 0% Default | | | | Disabled | +-----------------------------------------+------------------------+----------------------+ | 7 NVIDIA H100 80GB HBM3 Off | 00000000:DB:00.0 Off | 0 | | N/A 32C P0 71W / 700W | 1MiB / 81559MiB | 0% Default | | | | Disabled | +-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| | No running processes found | +-----------------------------------------------------------------------------------------+
How to proceed further and run the nccl test suit??