PROJECT NOT UNDER ACTIVE MANAGEMENT
This project will no longer be maintained by Intel.
Intel has ceased development and contributions including, but not limited to, maintenance, bug fixes, new releases, or updates, to this project.
Intel no longer accepts patches to this project.
If you have an ongoing need to use this project, are interested in independently developing it, or would like to maintain patches for the open source software community, please create your own fork of this project.
Contact: webadmin@linux.intel.com
Copyright (C) <2019-2022> Intel Corporation
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
https://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing,
software distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions
and limitations under the License.
SPDX-License-Identifier: Apache-2.0
The art of Automating Systematic Analysis through Telemetry Meta-Data.
Apache License Version 2.0, January 2004 http://www.apache.org/licenses/LICENSE-2.0
If you use the source code, please give credit to the authors.
- Title of program/source code: Rapid Automated-Analysis for Developers (RAAD)
- Date: 02-26-2018
- Code version: 1.0, Pre-Alpha
- Type: Source Code
- Sponsor(s):
- Intel Corporation
- Non-volatile Memory Storage Group (NSG)
- Labs
- Frank Hady
- Fellow of AI Systems Memory/Storage at Intel
- https://www.linkedin.com/in/frankhady/
- Pradeep Dubey
- Senior Fellow of Intel Labs at Intel
- https://www.linkedin.com/in/pradeep-dubey-a5592a53/
- Intel Corporation
- Primary Investigator, Architect, Designer, Director, and Lead Developer:
- Joseph (Joe) David Tarango
- Machine Learning Engineer of Non-volatile Memory Storage Group (NSG) at Intel
- http://josephtarango.com
- https://www.cs.ucr.edu/~jtarango/
- https://www.github.com/jtarango
- https://www.linkedin.com/in/joseph-tarango-451695a2
- Joseph (Joe) David Tarango
- Control Flag Architect, Artifical Intelligence Researcher of Intel
- Niranjan Hasabnis
- Business Unit Sponsor and Liaison
- Jim Baca
- (Former) Principal Engineer of Non-volatile Memory Storage Group (NSG) at Intel
- https://www.linkedin.com/in/jim-baca-657747
- Jim Baca
- Research Professor, University of California at Riverside
- Philip Brisk
- Internship Engineers Focused on RAAD:
- Daniel Garces
- Harvard Ph.D. Candidate
- https://www.linkedin.com/in/daniel-garcesb/
- Tyler Woods
- University of California at Riverside, Master's Candidate
- https://www.linkedin.com/in/tyler-woods-112354172/
- Rogelio Macedo
- University of California at Riverside, Master's Candidate
- https://www.linkedin.com/in/rmace001/
- Andrea Chamorro
- Colorado of University at Boulder Bachelor's Candidate
- https://www.linkedin.com/in/andrea-chamorroq/
- Sungkeun Kim
- Texas A&M Ph.D. Candidate
- https://www.linkedin.com/in/sungkeun-kim-20b898117/
- Zijia (Stella) Cao
- University of Chicago Master's Candidate
- https://www.linkedin.com/in/stella-zjcao/
- Daniel Garces
- Special Thanks to former Collaborator(s)
- Former, Machine Programming Research Director
- Justin Gottschlich
- (Former) Principal Artificial Intelligence Scientist of Intel Labs at Intel
- http://justingottschlich.com
- Justin Gottschlich
- Former, Machine Programming Research Director
- Acknowledgement(s), Contributor(s), and Champion(s):
- Abdullah Mueen: https://www.cs.unm.edu/~mueen/
- Abdullah Muzahid: http://people.tamu.edu/~abdullah.muzahid/index.html
- Anand Venkat: https://www.linkedin.com/in/anvenkat
- Andrew (Andy) Sainz : https://www.linkedin.com/in/andrew-sainz-b925a993
- Bradley (Brad) MacDonald: https://www.linkedin.com/in/brad-m
- Chetan Kumar Gupta
- Chin-Chia Michael Yeh: https://www.cs.ucr.edu/~myeh003/
- David Escamilla: https://www.linkedin.com/in/david-escamilla-709b193
- Eammon Keogh: https://www.cs.ucr.edu/~eamonn/
- Fangke Yeh: https://scholar.google.com/citations?user=6dp6cJ4AAAAJ
- Javier Turek: https://www.intel.com/content/www/us/en/research/researchers/javier-turek.html
- Jean Mary Madassery: https://www.linkedin.com/in/jean-mary-madassery-46461464
- Jesmin Jahan Tithi: https://www.intel.com/content/www/us/en/research/researchers/jesmin-jahan-tithi.html
- Jordan Howes: https://www.linkedin.com/in/jordan-howes-59360111
- Kaveh Kamgar: https://www.linkedin.com/in/kaveh-kamgar
- Krishnamurthy Viswanathan: https://www.linkedin.com/in/krishnamurthy-viswanathan-14b65a42
- Lukasz Tur: https://pl.linkedin.com/in/lukasz-tur-9574094
- Mejbah Alam: https://www.intel.com/content/www/us/en/artificial-intelligence/bios/mohammad-mejbah-ul-alam.html
- Michael Yeh
- Nesime Tatbul: https://people.csail.mit.edu/tatbul/
- Pallavi Dhumal
- Paul Peterson: https://www.linkedin.com/in/paul-petersen-41355011
- Phoung Tran
- Randal (Randy) Eike: https://www.linkedin.com/in/randal-eike-124931167
- Ryan Marcus: https://www.csail.mit.edu/person/ryan-marcus
- Shengtian Zhou: https://www.linkedin.com/in/shengtian-zhou
- Subhashini Sekaran
- Tim Kraska: https://people.csail.mit.edu/kraska/
- Timothy Mattson: https://www.intel.com/content/www/us/en/research/researchers/tim-mattson.html
- Vivek Sarkar
- Yan Zhu
- Zachery Zimmerman: https://www.linkedin.com/in/zpzim
- University of California at Riverside (UCR): https://www.ucr.edu/
Hello Fellow Developers,
The repository is currently in pre-alpha; which means there are many bugs, mixing of language sets (I.E. Python 2.x/3.x. and C/C++ standards), and unfinished code sets. The code is being released for reference and not all members may be participating. Please feel free to fix the code through pull requests.
- Please note for the best experience use Ubuntu 20.04 LTS x86_64 (https://releases.ubuntu.com/20.04/) as the development environment.
New development should have a unit test capability built in to ensure there are no regressions.
- Auto doxygen location
- RAAD\dox\build\index.html
- Docstring Style
- Example documentation execute order:
cd RAAD\dox\source\
python findClasses.py
cd ..
make clean
make html
An example python template of a can be seen in RAAD\src\software\utility\templateUtility.py
Telemetry is the state space snapshot which tightly-couple specialists to pertinent data, remotely, removing the cyber physical challenges with interacting on complex platforms. The immediate benefit is precise and rapid data extraction correlated to customer platforms. The purposeful subsequent benefit is reactive-proactive real-time analytics for monitoring of client platforms and data centers. The real-time processing of the data enables data mining, machine learning, and artificial intelligence. The application of these techniques is given in an instance of Intel SSDs and can be applied to technological eco-systems.
- .raadProfile (hidden folder) - Folder containing user preference and cache files.
- _dev_tools (Folder) - Developer assistant source code.
- data (folder) - Reference information for unit tests.
- dox (folder) - Code auto documentation generator.
- build (folder) - Active documentation build.
- doc (folder) - Contains various documentation with RAAD.
- architecture (folder) - Template of creating an architecture feature.
- images (folder) - Supporting diagrams.
- interns (folder) - Intern exit presentations.
- papers (folder) - White papers of RAAD.
- presentations (folder) - Research, development, and product instrumentation.
- source (folder) - source code to build documentation.
- scripts (folder) - Binary build, installer, and helping scripts.
- src (Folder) - Source Code.
- mpr (Folder) - Source Code for machine programming.
- autoperf (Folder) - External Library for performance analysis on code.
- controlflag (Folder) - External Library for software anomaly analysis.
- mism (Folder) - External Library for code similarity.
- software (Folder) - Software Source.
- access (Folder) - modules to access telemetry information.
- autoAI (Folder) - modules to construct and run neural nets dynamically in a multi-layer model.
- axon (Folder) - modules to upload telemetry content into a webpage tool used in searching of traits.
- container (Folder) - modules to dynamically manage data objects.
- cpt (Folder) - modules to dynamically classify and predict data properties.
- dAMP (Folder) - modules for domain automated machine programming.
- datacontrol (Folder) - Data control assistance modules.
- decode (Folder) - Decoder modules.
- ADP_UV (Folder) - Ctype auto parser generated decoder modules (not public).
- CDR_DA (Folder) - Ctype auto parser generated decoder modules (not public).
- DP (Folder) - modules for data preprocessing
- external (Folder) - External tools for workload generation.
- JIRA (Folder) - modules to use Atlassian database.
- MEP (Folder) - modules for media error prediction using the auto aggressive moving average model variants.
- mp (Folder) - modules for time series analysis through Matrix Profile.
- parse (Folder) - modules to decode a storage data container.
- probeTrace (Folder) - modules to interact with a Green Hill Debug Probe.
- sourceManagement (Folder) - source code interface.
- TSV (Folder) - modules to generate and visualize time series.
- twidl (Folder) - external library to import helper modules (not public).
- utility (Folder) - module template for new development.
- mpr (Folder) - Source Code for machine programming.