A Docker container to perform memory analyses on an isolated environment.
The only tools needed to run this container is docker-compose and git.
First you need to clone the repository to your local machine
$ git clone https://github.com/arthurcerveira/Video-Memory-Analysis-Environment.gitThen you'll need to create a directory video_sequences to store the videos(.yuv).
$ cd Video-Memory-Analysis-Environment
$ mkdir video_sequencesTo build the container and start the analysis you need to run the following commands
$ docker-compose build
$ docker-compose run -d --name running-mem mem-analysisOnce the execution is over, the results will be available in the Custom-Simulator directory on the host machine and the container can be removed.
$ docker rm running-memThe settings used for the analysis can be found in Custom-Simulator/custom_simulator.py.
The default values are:
# Routines
AUTOMATE_TRACE = True
GENERATE_TRACE_GRAPH = False
GENERATE_BLOCK_GRAPH = False
AUTOMATE_VTUNE = False
GENERATE_VTUNE_GRAPH = False
# Trace Reader
AUTOMATE_TRACE_OUTPUT = "automate_trace_output.txt"
# Vtune Reader
AUTOMATE_VTUNE_OUTPUT = "automate_vtune_output.txt"
# Encoder Paths
HM = "../hm-videomem/"
VTM = "../vtm-mem/"
HEVC = True
VVC = True
CONFIG = {"HEVC": {"Low Delay": HM + "cfg/encoder_lowdelay_main.cfg",
"Random Access": HM + "cfg/encoder_randomaccess_main.cfg"},
"VVC": {"Low Delay": VTM + "cfg/encoder_lowdelay_vtm.cfg",
"Random Access": VTM + "cfg/encoder_randomaccess_vtm.cfg"}}
VIDEO_CFG_PATH = {"HEVC": HM + "cfg/per-sequence/",
"VVC": VTM + "cfg/per-sequence/"}
VIDEO_SEQUENCES_PATH = "../video_sequences"
# Parameters
FRAMES = '17'
SEARCH_RANGE = ['96']The image on DockerHub uses the default settings and the video sequence BQSquare.
$ docker container run arthurcerveira/video-memory-analysis:1.0Example of results achieved by this container are available in this repository.
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