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Check if this returns correctly
/usr/local/cuda-10.0/samples/bin/x86_64/linux/release/deviceQuery
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/usr/local/cuda-10.0/samples/bin/x86_64/linux/release/deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 6 CUDA Capable device(s)
Device 0: "Tesla V100-PCIE-32GB"
CUDA Driver Version / Runtime Version 10.0 / 10.0
CUDA Capability Major/Minor version number: 7.0
Total amount of global memory: 32480 MBytes (34058272768 bytes)
(80) Multiprocessors, ( 64) CUDA Cores/MP: 5120 CUDA Cores
GPU Max Clock rate: 1380 MHz (1.38 GHz)
Memory Clock rate: 877 Mhz
Memory Bus Width: 4096-bit
L2 Cache Size: 6291456 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 7 copy engine(s)
Run time limit on kernels: No
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Enabled
Device supports Unified Addressing (UVA): Yes
Device supports Compute Preemption: Yes
Supports Cooperative Kernel Launch: Yes
Supports MultiDevice Co-op Kernel Launch: Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 20 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
Device 1: "Tesla V100-PCIE-32GB"
CUDA Driver Version / Runtime Version 10.0 / 10.0
CUDA Capability Major/Minor version number: 7.0
Total amount of global memory: 32480 MBytes (34058272768 bytes)
(80) Multiprocessors, ( 64) CUDA Cores/MP: 5120 CUDA Cores
GPU Max Clock rate: 1380 MHz (1.38 GHz)
Memory Clock rate: 877 Mhz
Memory Bus Width: 4096-bit
L2 Cache Size: 6291456 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 7 copy engine(s)
Run time limit on kernels: No
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Enabled
Device supports Unified Addressing (UVA): Yes
Device supports Compute Preemption: Yes
Supports Cooperative Kernel Launch: Yes
Supports MultiDevice Co-op Kernel Launch: Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 21 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
Device 2: "Tesla V100-PCIE-32GB"
CUDA Driver Version / Runtime Version 10.0 / 10.0
CUDA Capability Major/Minor version number: 7.0
Total amount of global memory: 32480 MBytes (34058272768 bytes)
(80) Multiprocessors, ( 64) CUDA Cores/MP: 5120 CUDA Cores
GPU Max Clock rate: 1380 MHz (1.38 GHz)
Memory Clock rate: 877 Mhz
Memory Bus Width: 4096-bit
L2 Cache Size: 6291456 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 7 copy engine(s)
Run time limit on kernels: No
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Enabled
Device supports Unified Addressing (UVA): Yes
Device supports Compute Preemption: Yes
Supports Cooperative Kernel Launch: Yes
Supports MultiDevice Co-op Kernel Launch: Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 57 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
Device 3: "Tesla V100-PCIE-32GB"
CUDA Driver Version / Runtime Version 10.0 / 10.0
CUDA Capability Major/Minor version number: 7.0
Total amount of global memory: 32480 MBytes (34058272768 bytes)
(80) Multiprocessors, ( 64) CUDA Cores/MP: 5120 CUDA Cores
GPU Max Clock rate: 1380 MHz (1.38 GHz)
Memory Clock rate: 877 Mhz
Memory Bus Width: 4096-bit
L2 Cache Size: 6291456 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 7 copy engine(s)
Run time limit on kernels: No
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Enabled
Device supports Unified Addressing (UVA): Yes
Device supports Compute Preemption: Yes
Supports Cooperative Kernel Launch: Yes
Supports MultiDevice Co-op Kernel Launch: Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 58 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
Device 4: "Tesla V100-PCIE-32GB"
CUDA Driver Version / Runtime Version 10.0 / 10.0
CUDA Capability Major/Minor version number: 7.0
Total amount of global memory: 32480 MBytes (34058272768 bytes)
(80) Multiprocessors, ( 64) CUDA Cores/MP: 5120 CUDA Cores
GPU Max Clock rate: 1380 MHz (1.38 GHz)
Memory Clock rate: 877 Mhz
Memory Bus Width: 4096-bit
L2 Cache Size: 6291456 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 7 copy engine(s)
Run time limit on kernels: No
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Enabled
Device supports Unified Addressing (UVA): Yes
Device supports Compute Preemption: Yes
Supports Cooperative Kernel Launch: Yes
Supports MultiDevice Co-op Kernel Launch: Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 136 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
Device 5: "Tesla V100-PCIE-32GB"
CUDA Driver Version / Runtime Version 10.0 / 10.0
CUDA Capability Major/Minor version number: 7.0
Total amount of global memory: 32480 MBytes (34058272768 bytes)
(80) Multiprocessors, ( 64) CUDA Cores/MP: 5120 CUDA Cores
GPU Max Clock rate: 1380 MHz (1.38 GHz)
Memory Clock rate: 877 Mhz
Memory Bus Width: 4096-bit
L2 Cache Size: 6291456 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 7 copy engine(s)
Run time limit on kernels: No
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Enabled
Device supports Unified Addressing (UVA): Yes
Device supports Compute Preemption: Yes
Supports Cooperative Kernel Launch: Yes
Supports MultiDevice Co-op Kernel Launch: Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 137 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
> Peer access from Tesla V100-PCIE-32GB (GPU0) -> Tesla V100-PCIE-32GB (GPU1) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU0) -> Tesla V100-PCIE-32GB (GPU2) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU0) -> Tesla V100-PCIE-32GB (GPU3) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU0) -> Tesla V100-PCIE-32GB (GPU4) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU0) -> Tesla V100-PCIE-32GB (GPU5) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU1) -> Tesla V100-PCIE-32GB (GPU0) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU1) -> Tesla V100-PCIE-32GB (GPU2) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU1) -> Tesla V100-PCIE-32GB (GPU3) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU1) -> Tesla V100-PCIE-32GB (GPU4) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU1) -> Tesla V100-PCIE-32GB (GPU5) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU2) -> Tesla V100-PCIE-32GB (GPU0) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU2) -> Tesla V100-PCIE-32GB (GPU1) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU2) -> Tesla V100-PCIE-32GB (GPU3) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU2) -> Tesla V100-PCIE-32GB (GPU4) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU2) -> Tesla V100-PCIE-32GB (GPU5) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU3) -> Tesla V100-PCIE-32GB (GPU0) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU3) -> Tesla V100-PCIE-32GB (GPU1) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU3) -> Tesla V100-PCIE-32GB (GPU2) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU3) -> Tesla V100-PCIE-32GB (GPU4) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU3) -> Tesla V100-PCIE-32GB (GPU5) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU4) -> Tesla V100-PCIE-32GB (GPU0) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU4) -> Tesla V100-PCIE-32GB (GPU1) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU4) -> Tesla V100-PCIE-32GB (GPU2) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU4) -> Tesla V100-PCIE-32GB (GPU3) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU4) -> Tesla V100-PCIE-32GB (GPU5) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU5) -> Tesla V100-PCIE-32GB (GPU0) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU5) -> Tesla V100-PCIE-32GB (GPU1) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU5) -> Tesla V100-PCIE-32GB (GPU2) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU5) -> Tesla V100-PCIE-32GB (GPU3) : Yes
> Peer access from Tesla V100-PCIE-32GB (GPU5) -> Tesla V100-PCIE-32GB (GPU4) : Yes
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 10.0, CUDA Runtime Version = 10.0, NumDevs = 6
Result = PASS
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gpu issues - Sample torch.device.py
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more log_device_placement.py ####https://www.tensorflow.org/guide/using_gpu import tensorflow as tf # Creates a graph. a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a') b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b') c = tf.matmul(a, b) # Creates a session with log_device_placement set to True. sess = tf.Session(config=tf.ConfigProto(log_device_placement=True)) # Runs the op. print(sess.run(c)) |
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You can background the each job as follows. In the example below, there are 3 jobs hitting a single gpu. We background a job by placing an ambasand (&) at the end of each command like this: python main.py --cfg <PATH>/config5.yml --gpu 0 & e.g: cat pbs.01 >>>>>>>>>>>>>>>>>>> #!/bin/bash -l #PBS -m abe #PBS -M abcde@griffithuni.edu.au #PBS -V #PBS -N testImage #PBS -q dljun@n060 #PBS -W group_list=deeplearning -A deeplearning #PBS -l select=1:ncpus=1:ngpus=1:mem=32gb,walltime=300:00:00 #PBS -j oe cd $PBS_O_WORKDIR module load anaconda/5.3.1py3 source activate tensorflow-gpu echo $CUDA_VISIBLE_DEVICES GPUNUM=`echo $CUDA_VISIBLE_DEVICES` #echo "python main.py --cfg cfg/config3.yml --gpu $GPUNUM &" python main.py --cfg cfg/config3.yml --gpu 0$GPUNUM & python main.py --cfg cfg/config4.yml --gpu 0$GPUNUM & python main.py --cfg cfg/config5.yml --gpu 0$GPUNUM & >>>>>>>>>>>>>>>>>>> Submit the job like this: qsub pbs.01 |
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