Hi ,
I am currently working on a TensorFlow python algorithm for object detection. The link is provided below.
My algorithm works fine and is compatible only with TensorFlow -1.0 version.
It was taking 17 seconds to detect objects in one frame.
On usage of the commands :
$ sudo nvpmodel -m 0
$ sudo ./jetson_clocks.sh
The time taken for detection is now 10 seconds.
The command - $sudo nvpmodel -q --verbose gives me the below output:
NVPM VERB: parsing done for /etc/nvpmodel.conf
NVPM VERB: Current mode: NV Power Mode: MAXN
0
NVPM VERB: PARAM CPU_ONLINE: ARG CORE_1: PATH /sys/devices/system/cpu/cpu1/online: REAL_VAL: 1 CONF_VAL: 1
NVPM VERB: PARAM CPU_ONLINE: ARG CORE_2: PATH /sys/devices/system/cpu/cpu2/online: REAL_VAL: 1 CONF_VAL: 1
NVPM VERB: PARAM CPU_ONLINE: ARG CORE_3: PATH /sys/devices/system/cpu/cpu3/online: REAL_VAL: 1 CONF_VAL: 1
NVPM VERB: PARAM CPU_ONLINE: ARG CORE_4: PATH /sys/devices/system/cpu/cpu4/online: REAL_VAL: 1 CONF_VAL: 1
NVPM VERB: PARAM CPU_ONLINE: ARG CORE_5: PATH /sys/devices/system/cpu/cpu5/online: REAL_VAL: 1 CONF_VAL: 1
NVPM VERB: PARAM CPU_A57: ARG MIN_FREQ: PATH /sys/devices/system/cpu/cpu0/cpufreq/scaling_min_freq: REAL_VAL: 2035200 CONF_VAL: 0
NVPM VERB: PARAM CPU_A57: ARG MAX_FREQ: PATH /sys/devices/system/cpu/cpu0/cpufreq/scaling_max_freq: REAL_VAL: 2035200 CONF_VAL: 2147483647
NVPM VERB: PARAM CPU_DENVER: ARG MIN_FREQ: PATH /sys/devices/system/cpu/cpu1/cpufreq/scaling_min_freq: REAL_VAL: 2035200 CONF_VAL: 0
NVPM VERB: PARAM CPU_DENVER: ARG MAX_FREQ: PATH /sys/devices/system/cpu/cpu1/cpufreq/scaling_max_freq: REAL_VAL: 2035200 CONF_VAL: 2147483647
NVPM VERB: PARAM GPU: ARG MIN_FREQ: PATH /sys/devices/17000000.gp10b/devfreq/17000000.gp10b/min_freq: REAL_VAL: 1300500000 CONF_VAL: 0
NVPM VERB: PARAM GPU: ARG MAX_FREQ: PATH /sys/devices/17000000.gp10b/devfreq/17000000.gp10b/max_freq: REAL_VAL: 1300500000 CONF_VAL: 2147483647
NVPM VERB: PARAM EMC: ARG MAX_FREQ: PATH /sys/kernel/nvpmodel_emc_cap/emc_iso_cap: REAL_VAL: 0 CONF_VAL: 0
Are there any further methods to reduce the detection time from 10seconds?
Kindly help
EDIT:
When I run $sudo ./tegrastats along with the object detection code.
During frame processing the tegrastats output is as below:
RAM 3326/7851MB (lfb 539x4MB) cpu [100%@2030,100%@2034,100%@2036,100%@2029,100%@2029,100%@2029] EMC 5%@1866 APE 150 GR3D 0%@1300
The CPU utilization is 100% whereas GPU usage is 0(GR3D).
Kindly help me in ways of how to utilize the GPU.
Thanks in advance.
Hi,
Please help us check these:
1. Make sure you have enabled TensorFlow GPU support.
You can find similar log if GPU mode is ON:
I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:0) → (device: 0, name: GP10B, pci bus id: 0000:00:00.0)
2. Check the device placement via this command and share with us:
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
Thanks.
Hi AastaLLL,
When I run the command
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
Device mapping: no known devices.
I tensorflow/core/common_runtime/direct_session.cc:257] Device mapping:
How can I enable TensorFlow GPU support?
I installed Tensorflow using the wheel files - tensorflow-1.0.1-cp27-cp27mu-linux_aarch64.whl and tensorflow-1.3.0-cp35-cp35m-linux_aarch64.whl
Thanks
Hi,
If TensorFlow-1.3/1.4 is acceptable for you, we recommend to use this wheel file:
Thanks.
Hi AastaLLL,
The code I am currently using doesn’t support v1.3/1.4.
Can you help me with Tensorflow GPU support for version 1.0.1
Thanks.
Hi,
Do you use the wheel file shared in this comment:
https://devtalk.nvidia.com/default/topic/1000717/jetson-tx2/tensorflow-on-jetson-tx2/post/5112792/#5112792
If yes, the user has enabled the GPU support.
Please remember to use the same CUDA/L4T version(Guess that is JetPack3.0) to make it run correctly.
Thanks.
Hi AastaLLL,
Thanks a lot for your support.
Yes I have used the same wheel file mentioned in this comment.I have JetPack 3.0 installed on the TX2 board.
$ nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2016 NVIDIA Corporation
Built on Mon_Mar_20_17:07:33_CDT_2017
Cuda compilation tools, release 8.0, V8.0.72
$head -n 1 /etc/nv_tegra_release
R28 (release), REVISION: 1.0, GCID: 9379712, BOARD: t186ref, EABI: aarch64,
Is there any changes I need to make to enable GPU?
Thanks.
Hi AastaLLL,
Yes The algorithm works fine after fixing the Tensorflow GPU installation.
Thankyou