So, I found a way to login to the computer with GPUs. I ran deviceQuery and it outputs the following :
./deviceQuery Starting…
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 4 CUDA Capable device(s)
Device 0: “Tesla K10.G1.8GB”
CUDA Driver Version / Runtime Version 9.0 / 8.0
CUDA Capability Major/Minor version number: 3.0
Total amount of global memory: 3527 MBytes (3698524160 bytes)
( 8) Multiprocessors, (192) CUDA Cores/MP: 1536 CUDA Cores
GPU Max Clock rate: 745 MHz (0.75 GHz)
Memory Clock rate: 2500 Mhz
Memory Bus Width: 256-bit
L2 Cache Size: 524288 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 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 2 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 PCI Domain ID / Bus ID / location ID: 0 / 38 / 0
Compute Mode:
< Exclusive Process (many threads in one process is able to use ::cudaSetDevice() with this device) >
Device 1: “Tesla K10.G1.8GB”
CUDA Driver Version / Runtime Version 9.0 / 8.0
CUDA Capability Major/Minor version number: 3.0
Total amount of global memory: 3527 MBytes (3698524160 bytes)
( 8) Multiprocessors, (192) CUDA Cores/MP: 1536 CUDA Cores
GPU Max Clock rate: 745 MHz (0.75 GHz)
Memory Clock rate: 2500 Mhz
Memory Bus Width: 256-bit
L2 Cache Size: 524288 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 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 2 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 PCI Domain ID / Bus ID / location ID: 0 / 39 / 0
Compute Mode:
< Exclusive Process (many threads in one process is able to use ::cudaSetDevice() with this device) >
Device 2: “Tesla K10.G1.8GB”
CUDA Driver Version / Runtime Version 9.0 / 8.0
CUDA Capability Major/Minor version number: 3.0
Total amount of global memory: 3527 MBytes (3698524160 bytes)
( 8) Multiprocessors, (192) CUDA Cores/MP: 1536 CUDA Cores
GPU Max Clock rate: 745 MHz (0.75 GHz)
Memory Clock rate: 2500 Mhz
Memory Bus Width: 256-bit
L2 Cache Size: 524288 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 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 2 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 PCI Domain ID / Bus ID / location ID: 0 / 42 / 0
Compute Mode:
< Exclusive Process (many threads in one process is able to use ::cudaSetDevice() with this device) >
Device 3: “Tesla K10.G1.8GB”
CUDA Driver Version / Runtime Version 9.0 / 8.0
CUDA Capability Major/Minor version number: 3.0
Total amount of global memory: 3527 MBytes (3698524160 bytes)
( 8) Multiprocessors, (192) CUDA Cores/MP: 1536 CUDA Cores
GPU Max Clock rate: 745 MHz (0.75 GHz)
Memory Clock rate: 2500 Mhz
Memory Bus Width: 256-bit
L2 Cache Size: 524288 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 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 2 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 PCI Domain ID / Bus ID / location ID: 0 / 43 / 0
Compute Mode:
< Exclusive Process (many threads in one process is able to use ::cudaSetDevice() with this device) >
Peer access from Tesla K10.G1.8GB (GPU0) → Tesla K10.G1.8GB (GPU1) : Yes
Peer access from Tesla K10.G1.8GB (GPU0) → Tesla K10.G1.8GB (GPU2) : Yes
Peer access from Tesla K10.G1.8GB (GPU0) → Tesla K10.G1.8GB (GPU3) : Yes
Peer access from Tesla K10.G1.8GB (GPU1) → Tesla K10.G1.8GB (GPU0) : Yes
Peer access from Tesla K10.G1.8GB (GPU1) → Tesla K10.G1.8GB (GPU2) : Yes
Peer access from Tesla K10.G1.8GB (GPU1) → Tesla K10.G1.8GB (GPU3) : Yes
Peer access from Tesla K10.G1.8GB (GPU2) → Tesla K10.G1.8GB (GPU0) : Yes
Peer access from Tesla K10.G1.8GB (GPU2) → Tesla K10.G1.8GB (GPU1) : Yes
Peer access from Tesla K10.G1.8GB (GPU2) → Tesla K10.G1.8GB (GPU3) : Yes
Peer access from Tesla K10.G1.8GB (GPU3) → Tesla K10.G1.8GB (GPU0) : Yes
Peer access from Tesla K10.G1.8GB (GPU3) → Tesla K10.G1.8GB (GPU1) : Yes
Peer access from Tesla K10.G1.8GB (GPU3) → Tesla K10.G1.8GB (GPU2) : Yes
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 9.0, CUDA Runtime Version = 8.0, NumDevs = 4, Device0 = Tesla K10.G1.8GB, Device1 = Tesla K10.G1.8GB, Device2 = Tesla K10.G1.8GB, Device3 = Tesla K10.G1.8GB
Result = PASS
Previously deviceQuery was freezing when I would submit a job from one computer outside the grid to the one above which has the GPUs.
Now the problem is that with basic example from JCuda, I still can’t get it to run. the program failed because glibc v 2.14 was not there. I installed it alongside existing one v 2.12 and added that to the LD_LIBRARY_PATH. Now the program does not crash but it’s freezing again.