nvenc accelerated ffmpeg not working

Accelerated Computing CUDA CUDA Programming and Performance
1

Hi all,

I’ve been trying to follow this guide to leverage nvenc to accelerate ffmpeg:

When running the following command:
ffmpeg -y -i input.avi -vcodec nvenc -b:v 5M -acodec copy output.mp4

I am seeing this error:
[/root/Development/ffmpeg/libavcodec/nvenc.c:1165]cuMemCpy2d(frame->data[1], (CUdeviceptr)NULL, frame->linesize[1], NULL, ctx->transferSurf.dptr, ctx->transferSurf.pitch / 2, ctx->transferSurf.width / 2, frame->height / 2, CU_MEMORYTYPE_HOST, CU_MEMORYTYPE_DEVICE) has returned CUDA error 1
[nvenc @ 0x39a6ba0] Failed to copy data to NVENC input buffer!

Some additional info:
root@3c2f5bd1f576:~# lspci | grep NVIDIA
04:00.0 3D controller: NVIDIA Corporation GK210GL [Tesla K80] (rev a1)
05:00.0 3D controller: NVIDIA Corporation GK210GL [Tesla K80] (rev a1)
83:00.0 3D controller: NVIDIA Corporation GK210GL [Tesla K80] (rev a1)
84:00.0 3D controller: NVIDIA Corporation GK210GL [Tesla K80] (rev a1)
root@3c2f5bd1f576:~# modinfo nvidia
filename: /lib/modules/4.4.6-coreos/video/nvidia.ko
alias: char-major-195-*
version: 352.39
supported: external
license: NVIDIA
alias: pci:v000010DEd00000E00svsdbc04sc80i00*
alias: pci:v000010DEdsvsdbc03sc02i00
alias: pci:v000010DEdsvsdbc03sc00i00
depends:
vermagic: 4.4.6-coreos SMP mod_unload
parm: NVreg_Mobile:int
parm: NVreg_ResmanDebugLevel:int
parm: NVreg_RmLogonRC:int
parm: NVreg_ModifyDeviceFiles:int
parm: NVreg_DeviceFileUID:int
parm: NVreg_DeviceFileGID:int
parm: NVreg_DeviceFileMode:int
parm: NVreg_UpdateMemoryTypes:int
parm: NVreg_InitializeSystemMemoryAllocations:int
parm: NVreg_UsePageAttributeTable:int
parm: NVreg_MapRegistersEarly:int
parm: NVreg_RegisterForACPIEvents:int
parm: NVreg_CheckPCIConfigSpace:int
parm: NVreg_EnablePCIeGen3:int
parm: NVreg_EnableMSI:int
parm: NVreg_MemoryPoolSize:int
parm: NVreg_RegistryDwords:charp
parm: NVreg_RmMsg:charp
parm: NVreg_AssignGpus:charp
root@3c2f5bd1f576:~# ls /dev/nvidia*
/dev/nvidia-uvm /dev/nvidia0 /dev/nvidia1 /dev/nvidia2 /dev/nvidia3 /dev/nvidiactl

As you can probably tell, I am running a privileged docker container on top of coreos.

Thanks!
-Simon