Hi Ross,
I was running this test:
Amber14_Benchmark_Suite/PME/JAC_production_NVE
srun -n 2 --mpi=pmi2 --cpu_bind=socket $AMBERHOME/bin/pmemd.cuda.MPI -O -i mdin.GPU -o mdout.2GPU -p prmtop -c inpcrd
Yes, a single GPU run completes normally.
I tried another test in that suite, and though the 2GPU test completed, it came up with different (nonsense) answers.
Maybe there's something wrong with the MPI/build. It's just Intel impi & "configure -cuda -mpi -noX11 intel"
Thanks,
Sarah
Two GPUs
R M S F L U C T U A T I O N S
NSTEP = 1000 TIME(PS) = 102.000 TEMP(K) = 6.13 PRESS = 0.0
Etot = 10445.2658 EKtot = 388.9169 EPtot = 10213.0555
BOND = 138.3458 ANGLE = 184.8487 DIHED = 119.1381
1-4 NB = 35.9507 1-4 EEL = 842.2853 VDWAALS = 9138.2936
EELEC = 2970.4534 EGB = 3580.7687 RESTRAINT = 0.0000
------------------------------------------------------------------------------
Single GPU:
R M S F L U C T U A T I O N S
NSTEP = 1000 TIME(PS) = 102.000 TEMP(K) = 0.91 PRESS = 0.0
Etot = 22.9288 EKtot = 57.4768 EPtot = 49.0089
BOND = 32.3643 ANGLE = 82.1033 DIHED = 80.2520
1-4 NB = 14.6668 1-4 EEL = 107.9454 VDWAALS = 148.9948
EELEC = 280.7436 EGB = 212.3126 RESTRAINT = 0.0000
------------------------------------------------------------------------------
On 2/12/16 1:16 PM, Ross Walker wrote:
> Hi Sarah,
>
> The error message doesn't tell a lot here unfortunately. The issue with GPU error messages is that if you have an array in memory that contains a NAN - say the force array got an infinite force - then things will be fine 'until' the code tries to upload or download from the GPU (or do a similar copy operation) - NAN's are not supported in these operations and thus you get the error that you see. The real error - e.g. 2 atoms sitting on top of each other occurred somewhere else entirely within the code. The net result is that just because the error is in the gpu_allreduce does not mean it is related to something wrong with the GPUs, or a driver issue or even a multi-GPU issue.
>
> What it likely means there is something wrong with the simulation itself that you are running. Have you tried running on just 1 GPU and see if that crashes as well (and also CPU?). Can you provide some more details about what you are actually simulating.
>
> All the best
> Ross
>
>> On Feb 12, 2016, at 10:42, Sarah Anderson <saraha.cray.com> wrote:
>>
>> Has anyone seen this message lately? I saw some notes about in mid 2015 but no particular fix suggested.
>>
>> This is with cuda 7.5 using a pair of K80 GPUS in peer-to-peer mode.
>>
>> It fails with all combinations of CUDA_VISIBLE_DEVICES 0,1 2,3
>>
>>> gpu_allreduce cudaDeviceSynchronize failed an illegal memory access was encountered
>>
>> |------------------- GPU DEVICE INFO --------------------
>> |
>> | Task ID: 0
>> | CUDA_VISIBLE_DEVICES: 0,1
>> | CUDA Capable Devices Detected: 2
>> | CUDA Device ID in use: 0
>> | CUDA Device Name: Tesla K80
>> | CUDA Device Global Mem Size: 11519 MB
>> | CUDA Device Num Multiprocessors: 13
>> | CUDA Device Core Freq: 0.82 GHz
>> |
>> |
>> | Task ID: 1
>> | CUDA_VISIBLE_DEVICES: 0,1
>> | CUDA Capable Devices Detected: 2
>> | CUDA Device ID in use: 1
>> | CUDA Device Name: Tesla K80
>> | CUDA Device Global Mem Size: 11519 MB
>> | CUDA Device Num Multiprocessors: 13
>> | CUDA Device Core Freq: 0.82 GHz
>> |
>> |--------------------------------------------------------
>>
>> |---------------- GPU PEER TO PEER INFO -----------------
>> |
>> | Peer to Peer support: ENABLED
>> |
>> |--------------------------------------------------------
>>
>>
>> Here is deviceQuery
>>
>> CUDA Device Query (Runtime API) version (CUDART static linking)
>>
>> Detected 2 CUDA Capable device(s)
>>
>> Device 0: "Tesla K80"
>> CUDA Driver Version / Runtime Version 7.5 / 7.5
>> CUDA Capability Major/Minor version number: 3.7
>> Total amount of global memory: 11520 MBytes (12079136768 bytes)
>> MapSMtoCores for SM 3.7 is undefined. Default to use 192 Cores/SM
>> MapSMtoCores for SM 3.7 is undefined. Default to use 192 Cores/SM
>> (13) Multiprocessors, (192) CUDA Cores/MP: 2496 CUDA Cores
>> GPU Clock rate: 824 MHz (0.82 GHz)
>> Memory Clock rate: 2505 Mhz
>> Memory Bus Width: 384-bit
>> L2 Cache Size: 1572864 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 Bus ID / PCI location ID: 5 / 0
>> Compute Mode:
>> < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
>>
>> Device 1: "Tesla K80"
>> CUDA Driver Version / Runtime Version 7.5 / 7.5
>> CUDA Capability Major/Minor version number: 3.7
>> Total amount of global memory: 11520 MBytes (12079136768 bytes)
>> MapSMtoCores for SM 3.7 is undefined. Default to use 192 Cores/SM
>> MapSMtoCores for SM 3.7 is undefined. Default to use 192 Cores/SM
>> (13) Multiprocessors, (192) CUDA Cores/MP: 2496 CUDA Cores
>> GPU Clock rate: 824 MHz (0.82 GHz)
>> Memory Clock rate: 2505 Mhz
>> Memory Bus Width: 384-bit
>> L2 Cache Size: 1572864 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 Bus ID / PCI location ID: 6 / 0
>> Compute Mode:
>> < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
>>> Peer access from Tesla K80 (GPU0) -> Tesla K80 (GPU1) : Yes
>>> Peer access from Tesla K80 (GPU1) -> Tesla K80 (GPU0) : Yes
>> deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 7.5, CUDA Runtime Version = 7.5, NumDevs = 2, Device0 = Tesla K80, Device1
>> = Tesla K80
>> Result = PASS
>>
>>
>>
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>
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Received on Fri Feb 12 2016 - 14:30:03 PST
