This was extracted (@ 2023-03-23 00:10) from a list of minutes
which have been approved by the Board.
Please Note
The Board typically approves the minutes of the previous meeting at the
beginning of every Board meeting; therefore, the list below does not
normally contain details from the minutes of the most recent Board meeting.
WARNING: these pages may omit some original contents of the minutes.
Meeting times vary, the exact schedule is available to ASF Members and Officers, search for "calendar" in the Foundation's private index page (svn:foundation/private-index.html).
Report was filed, but display is awaiting the approval of the Board minutes.
## Description: The mission of Apache TVM is the creation and maintenance of software related to compilation of machine learning models to run on a wide range of hardware platforms ## Issues: There are no issues requiring board attention. ## Membership Data: Apache TVM was founded 2020-11-17 (2 years ago) There are currently 64 committers and 25 PMC members in this project. The Committer-to-PMC ratio is roughly 2:1. Community changes, past quarter: - No new PMC members. Last addition was Josh Fromm on 2022-09-12. - Ashutosh Parkhi was added as committer on 2022-11-02 - Egor Churaev was added as committer on 2022-11-16 - Gavin Uberti was added as committer on 2022-12-02 ## Project Activity: Recent releases: - 0.10.0 was released on 2022-10-17. - 0.9.0 was released on 2022-07-19. Recent improvement highlights include: - Better support for meta-schedule. - Better support for hexagon devices. - New TVMScript parser - MicroTVM improvements ## Community Health: The projects merges 175 monthly. The community members continue to discuss modules proposals on various front. We are also in the process of organizing another community meeting in the incoming quarter. The initial call for proposal received 33 proposals and we plan to do another round of solicitations in the incoming new year.
## Description: The mission of Apache TVM is the creation and maintenance of software related to compilation of machine learning models to run on a wide range of hardware platforms ## Issues: There are no issues requiring board attention ## Membership Data: Apache TVM was founded 2020-11-17 (2 years ago) There are currently 61 committers and 24 PMC members in this project. The Committer-to-PMC ratio is roughly 8:3. Community changes, past quarter: - Wuwei Lin was added to the PMC on 2022-08-30 - David Riazati was added as committer on 2022-06-14 - Elen Kalda was added as committer on 2022-09-06 ## Project Activity: 0.9.0 was released on 2022-07-19. The project continues to make strides towards bringing new features to the community. Some of the highlights include: - New TVMScript parser support to enable meta-programming. - Improved support to qualcomm DSPs - Better PyTorch and code-generation interpolation - MicroNPU support The community also continues to explore new module support to enable dynamic shape and other needs. ## Community Health: The project maintains a monthly contribution of ~230 commits from 70 contributors. We continue to recognizes new members and welcome them to the community. We are also working together towards' TVMCon that brings together developers, users and researchers in the field to talk about overall machine learning compilation.
## Description: The mission of Apache TVM is the creation and maintenance of software related to compilation of machine learning models to run on a wide range of hardware platforms ## Issues: There are no issues requiring board attention. ## Membership Data: Apache TVM was founded 2020-11-17 (2 years ago) There are currently 58 committers and 23 PMC members in this project. The Committer-to-PMC ratio is roughly 8:3. Community changes, past quarter: - Krzysztof Parzyszek was added to the PMC on 2022-03-18 - Siyuan Feng was added to the PMC on 2022-03-20 - Gustavo Romero was added as committer on 2022-04-08 - Luke Hutton was added as committer on 2022-04-19 - Mehrdad Hessar was added as committer on 2022-04-05 - Ruihang Lai was added as committer on 2022-04-14 - xinqi was added as committer on 2022-04-14 - Xiyou Zhou was added as committer on 2022-04-23 ## Project Activity: Recent releases: 0.8.0 was released on 2021-11-25. The project community actively works towards improving the project in various areas, highlights include: - Improved support for qualcomm/ARM devices - Foundational improvements in arithmetic modules - Better usability and productivity via TVMScript. ## Community Health: The community continues to bring in new contributors. We have brought 8 new PMC members and committers in the past quarter. ~250 PRs are merged every month. There are also more organized planning through the RFC mechanism. We see a good amount of RFCs to support new features, frontends and hardware backends.
## Description: The mission of Apache TVM is the creation and maintenance of software related to compilation of machine learning models to run on a wide range of hardware platforms ## Issues: There are no issues requiring board attention. ## Membership Data: Apache TVM was founded 2020-11-17 (a year ago) There are currently 52 committers and 21 PMC members in this project. The Committer-to-PMC ratio is roughly 7:3. Community changes, past quarter: - Leandro Nunes was added to the PMC on 2022-03-01 - Andrew Luo was added as committer on 2022-01-11 - Bohan Hou was added as committer on 2022-01-06 - Chris Sullivan was added as committer on 2022-02-22 - Lily Orth-Smith was added as committer on 2022-02-28 - Eric Lunderberg was added as committer on 2021-12-17 ## Project Activity: Recent releases: 0.8.0 was released on 2021-11-25. The community continues to push TVM Unity -- the technical vision that we collectively set during TVMCon. Specifically with an emphasize on enabling collaboration and cross layer optimizations. Some of the recent highlights include: - Metaschedule, the latest automation mechanism is now fully upstreamed. - AOT compilation support for embedded devices - Hexagon DSP support - Overall performance improvements. ## Community Health: The community successfully held a virtual developer conference TVMCon in the past Dec. TVMCon attracted more than 1000 registered developers from all over the world. On average 200 PRs are merge every month from around 80 authors. We also start to see new features being proposed through the formal RFC process. We continue to welcome new committers and PMC members to the community.
## Description: The mission of Apache TVM is the creation and maintenance of software related to compilation of machine learning models to run on a wide range of hardware platforms ## Issues: There are no issues requiring board attention. ## Membership Data: Apache TVM was founded 2020-11-17 (a year ago) There are currently 47 committers and 20 PMC members in this project. The Committer-to-PMC ratio is roughly 2:1. Community changes, past quarter: - Andrew Reusch was added to the PMC on 2021-11-21 - Chris Sidebottom was added as committer on 2021-11-23 There are also ongoing nominations. ## Project Activity: Last release: 0.8.0 was released on 2021-11-25. The community works very hard to complete the 0.8.0 release. There are a lot of active development activities over the past quarter. Including, but not limited to: - Better TE, TIR, TVMScript support - More frontends (Paddle paddle) - Stablizing AutoScheduler - Stablizing Target system - TensorIR and meta-schedule support - TVMC and microTVM improvements - Improved Vulkan backend ## Community Health: The community has been receiving healthy contributions. Monthly about 70 authors contributing 150 commits. The community RFC process also starts to pick momentum, receiving RFCs from various contributors. We will hold the annual community conference TVMCon next week. This year we have one day tutorial and two days of talks with broad participation from both industry and academia.
## Description: The mission of Apache TVM is the creation and maintenance of software related to compilation of machine learning models to run on a wide range of hardware platforms ## Issues: There are no issues requiring board attention. ## Membership Data: Apache TVM was founded 2020-11-17 (10 months ago) There are currently 46 committers and 19 PMC members in this project. The Committer-to-PMC ratio is roughly 2:1. Community changes, past quarter: - Cody Yu was added to the PMC on 2021-07-13 - Junru Shao was added to the PMC on 2021-07-08 - Giuseppe Rossini was added as committer on 2021-09-04 - Manupa Karunaratne was added as committer on 2021-08-26 - Siyuan Feng was added as committer on 2021-09-04 ## Project Activity: Last release: 2020-10-09 The community starts the 0.8 release planning process. This release is going to contain a few major reworks of the TVM's internal architecture and bring next set of improvements. The project have been quite healthy and maintains the rate of 210 commits per month. Recent highlights include: - TensorIR scheduling system close to land in a month. - New frontend support: Oneflow, Paddle - Project API for micro tvm. - Automatic mixed precision support to enable customized floating points such as fp16. ## Community Health: We continue to bring new people from different organizations as committers and PMC members. The new RFC process(apache/tvm-rfcs) is now in-place. Overall the community reacted positively to the new RFC process as it allows more people to participate in the design proposal phase of the architecture. We also start to see a lot of collaborations around RFC discussions. The community also start to take a stab in improving code review process by update the review guidelines to contain more recommendations around code convention, documentation and consensus building. The proposed guideline improvements is voted and set to be incorporated into the contributor guide.
## Description: The mission of Apache TVM is the creation and maintenance of software related to compilation of machine learning models to run on a wide range of hardware platforms ## Issues: The project does not have issues that need board attention. ## Membership Data: Apache TVM was founded 2020-11-17 (7 months ago) There are currently 43 committers and 17 PMC members in this project. The Committer-to-PMC ratio is roughly 2:1. Community changes, past quarter: - Yao Wang was added to the PMC on 2021-04-05 - Andrew Reusch was added as committer on 2021-03-19 - Leandro Nunes was added as committer on 2021-05-07 - Steven Lyubomirsky was added as committer on 2021-05-04 - Trevor Morris was added as committer on 2021-05-21 ## Project Activity: Last release: 2020-10-09 The community is actively working on the new iteration towards the next release. The project have been quite healthy and maintains the rate of 150 commits per month. The improvement highlights include: - A major rework of the new TensorIR scheduling system. - uTVM to enable embedded device support - Better vulkan support to enable global coverage. - Better ONNX frontend support ## Community Health: The community is healthy. We continue to bring new people from different organizations as committers and PMC members. In our particular case, the PMC members follows only nominates people who are outside their own organization, encourage identification of candidates who are actively participating per apache way. The community members also continues to participate in design and general discussions Additionally, the community has voted to use a new RFC process that sends formal RFCs to a separate repo apache/tvm-rfcs after broad discussion among the community members.
## Description: The mission of Apache TVM is the creation and maintenance of software related to compilation of machine learning models to run on a wide range of hardware platforms ## Issues: No issue that needs board attention ## Membership Data: Apache TVM was founded 2020-11-17 (4 months ago) There are currently 39 committers and 16 PMC members in this project. The Committer-to-PMC ratio is roughly 5:2. Community changes, past quarter: - Leyuan Wang was added to the PMC on 2021-01-16 - Chenfan was added as committer on 2020-12-18 - Josh Fromm was added as committer on 2021-01-19 ## Project Activity: The community merged 130 pull requests from 69 authors in the past month. The improvements highlights includes: - Better vulkan and SPIRV support - Support of irregular control flow such as while loop - Initial support of TensorIR for tensor-core libraries - Various improvements to the Torch and Tensorflow frontends. ## Community Health: The developer community is healthy, with broad participations from various organizations. The community discussed about start experimenting a new RFC mechanism that opens pull request to a separate github repo (apache/tvm-rfcs, whose pull requests will be mirrored to dev@). This would allow reviews and tracking of the RFC more easily. Additionally, there are quite a few engaged discussion about the Device API, micro controller support, and Torchscript integeration. The community members also give talks in major workshops. The PMC is actively discussing new candidates for PMC and committership.
## Description: The mission of Apache TVM is the creation and maintenance of software related to compilation of machine learning models to run on a wide range of hardware platforms ## Issues: No issue that need board attention ## Membership Data: Apache TVM was founded 2020-11-17 (3 months ago) There are currently 39 committers and 16 PMC members in this project. The Committer-to-PMC ratio is roughly 5:2. Community changes, past quarter: - Leyuan Wang was added to the PMC on 2021-01-16 - Chenfan was added as committer on 2020-12-18 - Josh Fromm was added as committer on 2021-01-19 ## Project Activity: The project has been quite healthy in the past month. On main, 373 files have changed and there have been 14,511 additions and 4,001 deletions. The improvements come in areas include(but not limited to): - Better micro-controller support. - More documentation improvements. - Automatic scheduler enhancement to support more workloads. - Better test coverage and ## Community Health: 177 pull requests were bought up, and 135 of them were merged. Those contributions come from 55 authors. The community members are also actively engaged in RFC discussions, formalizing proposals for features like micro-controller support, compiler updates and accelerator support under the Apache way.
## Description: Apache TVM’s extensible full-stack framework enables deep learning applications to efficiently deploy across an array of hardware modules, platforms, and systems, including mobile phones, wearables, specialized chips, and embedded devices. ## Issues: There are no issues requiring board attention. ## Membership Data: Apache TVM was founded 2020-11-17 (2 months ago) There are currently 38 committers and 15 PMC members in this project. The Committer-to-PMC ratio is roughly 5:2. Community changes, past month: - The community is discussing and voting new PMC members. - Chenfan was added as committer on 2020-12-18 ## Project Activity: Software development activity: - We land the first complete version of the automatic scheduling code generation. - The community has been working on improving the robustness of the internals (better logging and error messaging). - Improvements to uTVM (micro-controller compilation support). - Last project release was v0.7.0 (2020-10-02), the community is working hard to push for the v0.8 release cycle. Meetups and Conferences: - Annual developer conference(see the community health) ## Community Health: Overall community health is good. The amount of PRs drop to 100 (was 150) monthly. But this is expected due to the holiday season. Followed by a successful announcement of the TLP. The community successfully held a three day virtual developer conference (https://tvmconf.org/) on Dec 2-4. Nearly 1000 people registered. The conference attracted talks from major industry users, such as AMD, ARM, AWS, Qualcomm, OctoML, Xilinx, Alibaba, Huawei, and academic contributors from UW, UC Berkeley, Cornell, UCLA, Beihang University. During the conference, the community celebrated the apache way and talked about their applications and contributions to the Apache TVM.
## Description: Apache TVM’s extensible full-stack framework enables deep learning applications to efficiently deploy across an array of hardware modules, platforms, and systems, including mobile phones, wearables, specialized chips, and embedded devices. ## Project Status: - Apache TVM graduated as a TLP last month - Community contribution are healthy, ~150 PRs merged last month - The community is working on new features on automatic scheduling, stabilizing the API, rust integration, micro-controllers, tensorflow and pytorch support ## Community - The community welcomed one new committer last month. There are also ongoing discussions about new committer. - The community is hosting an developer conference on Dec 2-4 https://tvmconf.org/ - Press release about TLP out, thanks to Sally! ## Releases: - Apache TVM 0.7.0 was released Oct 9 2020
WHEREAS, the Board of Directors deems it to be in the best interests of the Foundation and consistent with the Foundation's purpose to establish a Project Management Committee charged with the creation and maintenance of open-source software, for distribution at no charge to the public, related to compilation of machine learning models to run on a wide range of hardware platforms. NOW, THEREFORE, BE IT RESOLVED, that a Project Management Committee (PMC), to be known as the "Apache TVM Project", be and hereby is established pursuant to Bylaws of the Foundation; and be it further RESOLVED, that the Apache TVM Project be and hereby is responsible for the creation and maintenance of software related to compilation of machine learning models to run on a wide range of hardware platforms; and be it further RESOLVED, that the office of "Vice President, Apache TVM" be and hereby is created, the person holding such office to serve at the direction of the Board of Directors as the chair of the Apache TVM Project, and to have primary responsibility for management of the projects within the scope of responsibility of the Apache TVM Project; and be it further RESOLVED, that the persons listed immediately below be and hereby are appointed to serve as the initial members of the Apache TVM Project: * Tianqi Chen <tqchen@apache.org> * Timothy Chen <tnachen@apache.org> * Zhi Chen <zhic@apache.org> * Byung-Gon Chun <bgchun@apache.org> * Ziheng Jiang <ziheng@apache.org> * Furkan Kamaci <kamaci@apache.org> * YiZhi Liu <liuyizhi@apache.org> * Masahiro Masuda <masahi@apache.org> * Thierry Moreau <moreau@apache.org> * Jared Roesch <jroesch@apache.org> * Henry Saputra <hsaputra@apache.org> * Haichen Shen <haichen@apache.org> * Markus Weimer <weimer@apache.org> * Eddie Yan <eqy@apache.org> * Lianmin Zheng <lmzheng@apache.org> NOW, THEREFORE, BE IT FURTHER RESOLVED, that Tianqi Chen be appointed to the office of Vice President, Apache TVM, to serve in accordance with and subject to the direction of the Board of Directors and the Bylaws of the Foundation until death, resignation, retirement, removal or disqualification, or until a successor is appointed; and be it further RESOLVED, that the Apache TVM Project be and hereby is tasked with the migration and rationalization of the Apache Incubator TVM podling; and be it further RESOLVED, that all responsibilities pertaining to the Apache Incubator TVM podling encumbered upon the Apache Incubator PMC are hereafter Discharged. Special Order 7D, Establish the Apache TVM Project, was approved by Unanimous Vote of the directors present.
TVM is a full stack open deep learning compiler stack for CPUs, GPUs, and
specialized accelerators. It aims to close the gap between the
productivity- focused deep learning frameworks, and the performance- or
efficiency- oriented hardware backends.
TVM has been incubating since 2019-03-06.
### Three most important unfinished issues to address before graduating:
- Keep growing the community
### Are there any issues that the IPMC or ASF Board need to be aware of?
no
### How has the community developed since the last report?
TVM community has welcomed three new committers/PPMC members since last
report. There are also on-going new committer nominations. The community
is active and vibrate, with wide collaborations from many contributors.
The total number of contributors has grown to 440.
The community actively works to resolve the items under the guide of the
Apache maturity model.
### How has the project developed since the last report?
A lot of improvements have been made. Including automatic scheduling,
better documentations, command line support
See also our monthly reports for detailed improvements
- July https://discuss.tvm.apache.org/t/tvm-monthly-jul-2020/7570
- Aug https://discuss.tvm.apache.org/t/tvm-monthly-aug-2020/7791
### How would you assess the podling's maturity?
- [ ] Initial setup
- [ ] Working towards first release
- [X] Community building
- [X] Nearing graduation
- [ ] Other:
### Date of last release:
2020-07-10
The community is voting on a new release now
### When were the last committers or PPMC members elected?
2020-09-28
### Have your mentors been helpful and responsive?
Our mentors are super helpful.
### Is the PPMC managing the podling's brand / trademarks?
yes
### Signed-off-by:
- [X] (tvm) Byung-Gon Chun
Comments:
- [ ] (tvm) Sebastian Schelter
Comments:
- [X] (tvm) Henry Saputra
Comments: Peak for graduation.
- [ ] (tvm) Timothy Chen
Comments:
- [X] (tvm) Furkan Kamaci
Comments:
- [X] (tvm) Tianqi Chen
Comments:
- [X] (tvm) Markus Weimer
Comments: The project is ready for graduation.
### IPMC/Shepherd notes:
TVM is a full stack open deep learning compiler stack for CPUs, GPUs, and
specialized accelerators. It aims to close the gap between the productivity-
focused deep learning frameworks, and the performance- or efficiency-
oriented hardware backends.
TVM has been incubating since 2019-03-06.
### Three most important unfinished issues to address before graduating:
1. Keep growing the community
### Are there any issues that the IPMC or ASF Board need to be aware of?
no
### How has the community developed since the last report?
TVM community has welcomed four new committers/PPMC members since last
report. There are also on-going new committer nominations.
The community is active and vibrate, with wide collaborations from many
contributors. The total number of contributors has grown to 387.
The community actively works to resolve the items under the guide of the
Apache maturity model
https://docs.google.com/document/d/18nyAH-fcptVezAxPQe6H3FeTKPRkujOp1tc1YRSP
Lok/edit?usp=sharing
### How has the project developed since the last report?
A lot of improvements have been made. Including wasm/webgpu backend,
performance improvement,
operator/backend coverage, codebase refactor
See also our monthly reports for detailed improvements
- Mar https://discuss.tvm.ai/t/tvm-monthly-march-2020/6199
- Apr https://discuss.tvm.ai/t/tvm-monthly-april-2020/6570
- May https://discuss.tvm.ai/t/tvm-monthly-may-2020/6992
### How would you assess the podling's maturity?
- [ ] Initial setup
- [ ] Working towards first release
- [X] Community building
- [X] Nearing graduation
- [ ] Other:
### Date of last release:
2019-12-1
The community is voting on a new release now
### When were the last committers or PPMC members elected?
No answer.
### Have your mentors been helpful and responsive?
Our mentors are super helpful.
### Is the PPMC managing the podling's brand / trademarks?
yes
### Signed-off-by:
- [X] (tvm) Byung-Gon Chun
Comments:
- [ ] (tvm) Sebastian Schelter
Comments:
- [X] (tvm) Henry Saputra
Comments: Community is growing and healthy
- [ ] (tvm) Timothy Chen
Comments:
- [X] (tvm) Furkan Kamaci
Comments:
- [X] (tvm) Tianqi Chen
Comments:
- [X] (tvm) Markus Weimer
Comments: Looking forward to graduation soon.
### IPMC/Shepherd notes:
TVM is a full stack open deep learning compiler stack for CPUs, GPUs, and
specialized accelerators. It aims to close the gap between the productivity-
focused deep learning frameworks, and the performance- or efficiency-
oriented hardware backends.
TVM has been incubating since 2019-03-06.
### Three most important unfinished issues to address before graduating:
1. Keep growing the community
2. Make a few more Apache releases
3. Improve documentations
### Are there any issues that the IPMC or ASF Board need to be aware of?
no
### How has the community developed since the last report?
TVM community has welcomed two new committers/PPMC members since last
report.
There are also two on-going new committer nomination that will close in a
week.
The community hosted many meetups and an annual developer conference with
more than 200+ attendees.
These contents are made publically available as per apache way.
This has been a great year for us doing the Apache way and grow the
community.
The community has grown 70% in terms of number of contributors and
committers,
while these statistics do not necessarily indicate success, they suggest
we are on the right track.
### How has the project developed since the last report?
We made our first Apache release. Thanks to the help of IPMC members, in
particular Justin, we were able to
hold the Apache standard and release without using the WIP disclaimer
A lot of improvements have been made. Including TensorCore support,
embedded system support and performance improvements
See also our monthly report for detailed improvements
- Sep https://discuss.tvm.ai/t/tvm-monthly-september-2019/4219
- Oct https://discuss.tvm.ai/t/tvm-monthly-oct-2019/4587
- Nov https://discuss.tvm.ai/t/tvm-monthly-nov-2019/5038
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [ ] Initial setup
- [ ] Working towards first release
- [x] Community building
- [x] Nearing graduation
- [ ] Other:
### Date of last release:
2019-12-1
### When were the last committers or PPMC members elected?
Dec 1 2019
### Have your mentors been helpful and responsive?
Our mentors are super helpful.
### Is the PPMC managing the podling's brand / trademarks?
We have yet check with the VP.
Given the long history of the project, we want to keep the name,
will reach out to brand formally.
### Signed-off-by:
- [x] (tvm) Byung-Gon Chun
Comments: Great progress! Good job on the first Apache release!
- [ ] (tvm) Sebastian Schelter
Comments:
- [X] (tvm) Henry Saputra
Comments: Community is healthy and congrats on the first release under ASF
- [ ] (tvm) Timothy Chen
Comments:
- [X] (tvm) Furkan Kamaci
Comments:
- [x] (tvm) Tianqi Chen
Comments:
- [x] (tvm) Markus Weimer
Comments: With the first release done, we should look towards
graduation.
### IPMC/Shepherd notes:
Justin Mclean: I think it may be a little too early to consider
graduation. Has the podling filling the the optional maturity model,
doing so may point out when there's still more work to do.
TVM is a full stack open deep learning compiler stack for CPUs, GPUs, and
specialized accelerators. It aims to close the gap between the productivity-
focused deep learning frameworks, and the performance- or efficiency-
oriented hardware backends.
TVM has been incubating since 2019-03-06.
### Three most important unfinished issues to address before graduating:
1. Source code and website migration to ASF infra
2. Make the first Apache release
3. Continue to grow the community
### Are there any issues that the IPMC or ASF Board need to be aware of?
No
### How has the community developed since the last report?
TVM community has welcomed four committers since last report.
We also made our first presentation at ApacheCon NA.
### How has the project developed since the last report?
The project has been quite health, with ~120 pull requests being merged
every months.
These pull requests are authored by a diverse set of contributors(~50
authors last month).
Some highlights of recent developments:
- New integer analysis infrastructure
- Initial computation support
- Support for running quanitized models
For detailed information about the project development, please refer to
the
monthly TVM community's monthly summary:
- Oct: https://discuss.tvm.ai/t/tvm-monthly-september-2019/4219
- Aug: https://discuss.tvm.ai/t/tvm-monthly-august-2019/3904
- July: https://discuss.tvm.ai/t/tvm-monthly-july-2019/3600
- June: https://discuss.tvm.ai/t/tvm-monthly-june-2019/3202
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [x] Initial setup
- [x] Working towards first release
- [x] Community building
- [ ] Nearing graduation
- [ ] Other:
### Date of last release:
no release yet
### When were the last committers or PPMC members elected?
Sep 30 2019
### Have your mentors been helpful and responsive?
Mentors are very helpful in providing helpful guidance.
### Signed-off-by:
- [X] (tvm) Byung-Gon Chun
Comments: great progress
- [ ] (tvm) Sebastian Schelter
Comments:
- [X] (tvm) Henry Saputra
Comments: Will start working on repo migration
- [ ] (tvm) Timothy Chen
Comments:
- [X] (tvm) Furkan Kamaci
Comments:
- [x] (tvm) Tianqi Chen
Comments:
### IPMC/Shepherd notes:
TVM is a full stack open deep learning compiler stack for CPUs, GPUs, and
specialized accelerators. It aims to close the gap between the productivity-
focused deep learning frameworks, and the performance- or efficiency-
oriented hardware backends.
TVM has been incubating since 2019-03-06.
### Three most important unfinished issues to address before graduating:
1. Source code and website migration to ASF infra
2. Make the first Apache release
3. Continue to grow the community
### Are there any issues that the IPMC or ASF Board need to be aware of?
N/A
### How has the community developed since the last report?
TVM community has welcomed one committer in the past month.
### How has the project developed since the last report?
Summary statistics: In the past month authors have pushed 142 commits to
master and 142 commits to all branches. On master, 421 files have changed
and there have been 22,680 additions and 5,388 deletions.
Some highlights of recent developments:
- Robust coverage of windows support.
- Improvements in the integer simplifier interface.
- Major improvements in high level ir(relay) support
- For detailed information about the project development, please refer to
the monthly TVM community's monthly summary:
- May: https://discuss.tvm.ai/t/tvm-monthly-may-2019/2793
- June: https://discuss.tvm.ai/t/tvm-monthly-june-2019/3202
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [x] Initial setup
- [x] Working towards first release
- [x] Community building
- [ ] Nearing graduation
- [ ] Other:
### Date of last release:
N/A
### When were the last committers or PPMC members elected?
June 13 2019
### Have your mentors been helpful and responsive?
Mentors are very helpful in providing guidance.
### Signed-off-by:
- [X] (tvm) Byung-Gon Chun
Comments:
- [ ] (tvm) Sebastian Schelter
Comments:
- [X] (tvm) Henry Saputra
Comments: Working on migration or resources to ASF infra and managed
resources. But the community still growing and active.
- [ ] (tvm) Timothy Chen
Comments:
- [X] (tvm) Furkan Kamaci
Comments:
- [X] (tvm) Markus Weimer
Comments:
### IPMC/Shepherd notes:
TVM is a full stack open deep learning compiler stack for CPUs, GPUs, and
specialized accelerators. It aims to close the gap between the productivity-
focused deep learning frameworks, and the performance- or
efficiency-oriented
hardware backends.
TVM has been incubating since 2019-03-06.
### Three most important unfinished issues to address before graduating:
1. Source code and website migration to ASF infra
2. Make the first Apache release
3. Continue to grow the community
### Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be
aware of?
No answer.
### How has the community developed since the last report?
TVM community has welcomed one PPMC member in the past month. There is
also ongoing votes about adding new committers.
### How has the project developed since the last report?
Summary statistics: in the past month, 44 contributors have pushed 98
commits to master and 98 commits to all branches. On master, 366 files
have changed and there have been 21,156 additions and 2,810 deletions.
The contributions covers areas including documentations, bugfixes, user
interface and backend hardware support.
Some highlights of recent developments:
- More robust frontend support to support various machine learning models.
- Cycle accurate simulation to make it easy to add new architecture
backends.
- Quantized models to enable deployment to embedded devices.
For detailed information about the project development, please refer to
the monthly TVM community's monthly summary:
- April: https://discuss.tvm.ai/t/tvm-monthly-april-2019/2426
- May: https://discuss.tvm.ai/t/tvm-monthly-may-2019/2793
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [x] Initial setup
- [x] Working towards first release
- [x] Community building
- [ ] Nearing graduation
- [ ] Other:
### Date of last release:
no release yet
### When were the last committers or PPMC members elected?
May 23rd
### Have your mentors been helpful?
Mentors are very helpful in helping to set up the podling and provide
helpful guidance.
### Signed-off-by:
- [X] (tvm) Markus Weimer
Comments:
- [X] (tvm) Byung-Gon Chun
Comments:
- [ ] (tvm) Sebastian Schelter
Comments:
- [X] (tvm) Henry Saputra
Comments:
- [ ] (tvm) Timothy Chen
Comments:
- [X] (tvm) Furkan Kamaci
Comments:
### IPMC/Shepherd notes:
Dave Fisher: This already busy project and community is just getting
started in the Incubator.
They look to be on the right track. They have some resources which may
require a VM.
I suggested that they reach out to Infra on Slack for some answers.
It's good to see mentor engagement.
TVM is a full stack open deep learning compiler stack for CPUs, GPUs, and specialized accelerators. It aims to close the gap between the productivity- focused deep learning frameworks, and the performance- or efficiency-oriented hardware backends. TVM has been incubating since 2019-03-06. Three most important unfinished issues to address before graduating: 1. Source code and website migration to ASF infra 2. Make the first Apache release 3. Continue to grow the community Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be aware of? How has the community developed since the last report? TVM community has welcomed one new committer in the past month How has the project developed since the last report? In the past month, 51 contributors have pushed 109 commits to master and 109 commits to all branches. On master, 1,763 files have changed and there have been 44,070 additions and 13,852 deletions. See detailed monthly report - Mar: https://discuss.tvm.ai/t/tvm-monthly-march-2019/2083 - April: https://discuss.tvm.ai/t/tvm-monthly-april-2019/2426 How would you assess the podling's maturity? Please feel free to add your own commentary. [x] Initial setup [x] Working towards first release [x] Community building [ ] Nearing graduation [ ] Other: Date of last release: not yet When were the last committers or PPMC members elected? 2019 April 22 Have your mentors been helpful and responsive or are things falling through the cracks? In the latter case, please list any open issues that need to be addressed. Mentors are very helpful in helping to set up the podling and provide helpful guidance. Signed-off-by: [X] (tvm) Markus Weimer Comments: [ ](tvm) Byung-Gon Chun Comments: [ ](tvm) Sebastian Schelter Comments: [X](tvm) Henry Saputra Comments: [ ](tvm) Timothy Chen Comments: [X](tvm) Furkan Kamaci Comments: IPMC/Shepherd notes:
TVM is a full stack open deep learning compiler stack for CPUs, GPUs, and
specialized accelerators. It aims to close the gap between the productivity-
focused deep learning frameworks, and the performance- or
efficiency-oriented
hardware backends.
TVM has been incubating since 2019-03-06.
Three most important unfinished issues to address before graduating:
1. Finish the IP clearance
2. Make the first Apache release
3. Continue to grow the community
Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be
aware of?
None
How has the community developed since the last report?
- TVM PMC has been fully transitioned to private@
- The development conversations are mirrored to dev@
- TVM community has welcomed two new committers in the past month
See more in https://github.com/dmlc/tvm/search?q=COMMUNITY&type=Issues
NOTE: due to the transition, the vote of the new committers were done in
the pre-apache PMC private list with our mentors as observers.
We are doing procedural votes to bring these committers formally to
Apache soon.
How has the project developed since the last report?
In the past month, 47 contributors have pushed 138 commits.
On master, 480 files have changed and there have been
18,529 additions and 4,290 deletions.
See details in our monthly report
Mar: https://discuss.tvm.ai/t/tvm-monthly-march-2019/2083/2
Feb: https://discuss.tvm.ai/t/tvm-monthly-feb-2019/1801
How would you assess the podling's maturity?
Please feel free to add your own commentary.
[X] Initial setup
[X] Working towards first release
[X] Community building
[ ] Nearing graduation
[ ] Other:
Date of last release:
None yet
When were the last committers or PPMC members elected?
2019 Mar 15
Have your mentors been helpful and responsive or are things falling
through the cracks? In the latter case, please list any open issues
that need to be addressed.
Mentors are very helpful in helping to set up the podling and provide
helpful guidances.
Signed-off-by:
[X](tvm) Byung-Gon Chun
Comments:
[X](tvm) Sebastian Schelter
Comments:
[X](tvm) Henry Saputra
Comments:
[X](tvm) Timothy Chen
Comments:
[X](tvm) Furkan Kamaci
Comments:
[X](tvm) Markus Weimer
Comments:
IPMC/Shepherd notes: