| RDMA verification | |
| This work assumes there are two nodes to run iscsi target/initiator environment. | |
| -------------------------------------------------------------------------------------------------------- | |
| Load the RDMA drivers using the following command line | |
| /etc/init.d/openibd start | |
| If one is using the InfiniBand transport and he doesn't have a managed switch in the subnet, he has to start the Subnet Manager (SM). Doing this in one of the machines in the subnet is enough, this can be done with the following command line | |
| /etc/init.d/opensmd start | |
| -------------------------------------------------------------------------------------------------------- | |
| Verify that traffic is working |
| /* Copyright (c) 2017 Mozilla */ | |
| /* Copyright (c) 2017 Jan Weiß */ | |
| /* | |
| Redistribution and use in source and binary forms, with or without | |
| modification, are permitted provided that the following conditions | |
| are met: | |
| - Redistributions of source code must retain the above copyright | |
| notice, this list of conditions and the following disclaimer. |
| Optimization For Android Platform | |
| ================================= | |
| best way is to add only the code that you use in the actual model. | |
| 1.python tensorflow/python/tools/print_selective_registration_header.py --graphs="xxx.pb" > ops_to_register.h" | |
| ops_to_register.h -> Recompile the code by inserting the generated header. | |
| cp ops_to_register.h tensorflow/core/framework/ | |
| When you build a bazel --copts=-DSELECTIVE_REGISTRATION added | |
Building Tensorflow from source on Ubuntu 16.04LTS for maximum performance:
TensorFlow is now distributed under an Apache v2 open source license on GitHub.
On Ubuntu 16.04LTS+:
Step 1. Install NVIDIA CUDA:
To use TensorFlow with NVIDIA GPUs, the first step is to install the CUDA Toolkit as shown:
The git command-line utility has plenty of inconsistencies http://steveko.wordpress.com/2012/02/24/10-things-i-hate-about-git/
A GUI like http://sourcetreeapp.com is often helpful, but staying on the command line usually quicker. This is a list of the commands I use most frequently, listed by funcional category:
git status list which (unstaged) files have changed
| /* | |
| * File format: raw, PCM s16le | |
| * Resample 44100 Hz ./audio.raw to 16000 Hz ./audio_resampled.raw: | |
| * gcc -g resampler.c -o resampler | |
| * ./resampler | |
| */ | |
| #include <stdlib.h> | |
| #include <stdio.h> | |
| #include <memory.h> |
| 1. Execute make first. This will result in a netlinkKernel.ko output among many others. | |
| 2. Execute $ gcc netlinkUser.c -o netlinkUser | |
| 3. Insert kernel module by :$ sudo insmod netlinkKernel.ko | |
| 4. Run ./netlinkUser to see message and run dmesg to see debug messages | |
| 5. Remove module by : $ sudo rmmod netlinkKernel | |
| 6. Finally make clean to remove output files. |
