Difference between revisions of "GSOC 2018 Ideas"
(→Project Description) |
(add data frames + jupyter d kernel) |
||
Line 67: | Line 67: | ||
==== Proposed Project Mentor: [http://wiki.dlang.org/GSOC_mentors#Johan_Engelen Johan Engelen] ==== | ==== Proposed Project Mentor: [http://wiki.dlang.org/GSOC_mentors#Johan_Engelen Johan Engelen] ==== | ||
+ | |||
+ | === Data frames === | ||
+ | |||
+ | Pandas, R and Julia have made [https://github.com/mobileink/data.frame/wiki/What-is-a-Data-Frame%3F data frames] very popular. | ||
+ | As D is getting more interest from data scientist (e.g. [eBay http://tech.adroll.com/blog/data/2014/11/17/d-is-for-data-science.html] or [AdRoll http://tech.adroll.com/blog/data/2014/11/17/d-is-for-data-science.html]) it would be very beneficial to use one language for the entire data analysis pipeline - especially considering that D (in contrast to popular languages like Python, R or Julia) - is compiled to native machine code and gets optimized by the sophisticated LLVM backend. | ||
+ | |||
+ | === Jupyter notebook D kernel === | ||
+ | |||
+ | The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. | ||
+ | Jupyter notebooks are extremely popular among data scientist as they allow interactive progress and exploring a solution step by step. | ||
+ | With a bit of work, a statically compiled language can be used in an interactive notebook e.g. [Cling https://blog.jupyter.org/interactive-workflows-for-c-with-jupyter-fe9b54227d92] and Go with | ||
+ | [https://github.com/gopherdata/gophernotes gophernotes]. | ||
+ | Apart from being useful to data scientist, a Jupyter D kernel would allow an intuitive exploration of the language for newcomers and people starting with new libraries. | ||
+ | |||
+ | Existing works: | ||
+ | - [https://github.com/dlang-community/drepl drepl] - simple REPL for D | ||
+ | - [https://github.com/DlangScience/PydMagic PydMagic] - allows to write PyD extension in a notebook. | ||
=== SDC Project - D Compiler as a Library === | === SDC Project - D Compiler as a Library === |
Revision as of 03:31, 23 January 2018
This is the D Google Summer of Code page for 2018 - it is currently under construction. If you are interested in participating in the 2018 GSOC as either a student or mentor, and want to do something related to D, please feel free to contact us at (gsoc dot dlang dot io).
Contents
- 1 Timeline
- 2 Ideas
- 2.1 Mir Project
- 2.2 gRPC in D
- 2.3 ros2 client
- 2.4 Data frames
- 2.5 Jupyter notebook D kernel
- 2.6 SDC Project - D Compiler as a Library
- 2.7 FlatBuffers Support and/or Improved Protocol Buffer Support
- 2.8 Lowerer
- 2.9 fork()-based Garbage Collector
- 2.10 Linux debugger
- 2.11 Who's (Using) Who?
- 2.12 Phobos: D Standard Library
- 2.13 DUB: D's package manager
- 2.14 Propose your own project
- 3 Ideas From Previous Years
- 4 Tips for students
- 5 Tips for Mentors
Timeline
The timeline for GSoC 2018 can be found here.
Ideas
Plenty of challenging and important projects exist in the D world. They range from writing new or improving existing modules of D's standard library (Phobos), working on its compilers (Compilers), shaping GUI libraries for D, integrating D with other languages and more.
Mir Project
Project Description
The Mir project is developing numerical libraries for the upcoming numeric packages of the Dlang standard library. The are numerous projects an interested student could pursue:
- University project. Your GSoC project can be combined with your scientific research.
- ndslice>-<Julia integration
- ndslice>-<NumPy integration
- General purpose BetterC libraries
- I/O betterC Dlang library
- Async betterC Dlang library
- String and format betterC library
- mir-cpuid
- ARM support
- Advanced OS specific support
- mir-glas
- BLAS Level 2 subprograms
- One BLAS Level 3 subprogram. It is OK to do only one! But it must be faster then OpenBLAS, and not slower then Intel MKL.
- Multithreading support for BLAS Level 2
- Multithreading support for BLAS Level 3
You can get more details on projects related to Mir here.
Its Good To Know
To work on the Mir you should be proficient with one of:
- C
- C++
- LLVM
- Fortran
- Experience with D is not essential.
To work on the Mir project requires a responsible and self-motivated student.
gRPC in D
gRPC is a high performance, open-source universal RPC framework. It works across languages and platforms by automatically generating idiomatic client and server stubs in a variety of languages. The goal of this project is to add D to the supported languages of gRPC and thus allow the use of D in gRPCs stacks.
Proposed Project Mentor: Ali Çehreli
ros2 client
Robot Operating System (ROS) is robotics middleware (i.e. collection of software frameworks for robot software development). It provides services designed for heterogeneous computer cluster such as hardware abstraction, low-level device control, implementation of commonly used functionality, message-passing between processes, and package management. A ros2 client package would allow controlling robots in a high-level, modern language without loosing on performance.
- functionality and API equivalent to [ROS2 C++ client library](https://github.com/ros2/rclcpp) (C++ client library has most advanced feature set right now)
- functionality to support building D client library packages
A short technical summary can be found here.
Proposed Project Mentor: Johan Engelen
Data frames
Pandas, R and Julia have made data frames very popular. As D is getting more interest from data scientist (e.g. [eBay http://tech.adroll.com/blog/data/2014/11/17/d-is-for-data-science.html] or [AdRoll http://tech.adroll.com/blog/data/2014/11/17/d-is-for-data-science.html]) it would be very beneficial to use one language for the entire data analysis pipeline - especially considering that D (in contrast to popular languages like Python, R or Julia) - is compiled to native machine code and gets optimized by the sophisticated LLVM backend.
Jupyter notebook D kernel
The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. Jupyter notebooks are extremely popular among data scientist as they allow interactive progress and exploring a solution step by step. With a bit of work, a statically compiled language can be used in an interactive notebook e.g. [Cling https://blog.jupyter.org/interactive-workflows-for-c-with-jupyter-fe9b54227d92] and Go with gophernotes. Apart from being useful to data scientist, a Jupyter D kernel would allow an intuitive exploration of the language for newcomers and people starting with new libraries.
Existing works: - drepl - simple REPL for D - PydMagic - allows to write PyD extension in a notebook.
SDC Project - D Compiler as a Library
Project Description
The SDC project (https://github.com/deadalnix/SDC) is an effort to provide a D compiler as a library. Any ideas to further the development of this project are welcome, but for a student who would like a specific project we propose the following
- Start by implementing with @property feature of D. This feature will allow a D programmer to create functions that are called using the same syntax as variable access.
- Using the @property feature the student will be able to implement the runtime support for slices and associative arrays. The operations to implement are as follows:
- Implement arrray operations like concatenation and appending, and implement a sound memory management strategy for the underlying data.
- Implement a generic and efficient hash table. The data structure and algorithms used must be flexibile enough to be adapted to any type of data that might be stored in the table. A concurrent version of the table is need for shared data.
- Finally, the student will implement masquerading of D syntax into calls for the runtime.
- Integrate LLVM's new JIT infrastructure in SDC, the On-Request Compilation JIT (ORCJit) API. This would simplify the implementation of certain D features such as Compile Time Function Evaluation (CTFE) for SDC.
Its Good To Know
- Please watch Amaury's DConf talk on SDC.
- SDC is developed in D (of course) so you will need to be proficient in D by the time you start coding.
- You should have taken at least one course on compilers, or at the least be willing to educate yourself in this regard. There is a decent course availabe through Coursera https://www.coursera.org/course/compilers
- You should familiarize yourself with classicial data structures for arrays and have knowledge of various schemes for table implementations, (it is worthwhile to read up on hopscotch and robin hood hashing).
- SDC uses LLVM for code generation, so some familiarity with LLVM will be required (see http://llvm.org/docs/tutorial/index.html).
Proposed Project Mentor: Amaury Sechet
FlatBuffers Support and/or Improved Protocol Buffer Support
Project Description
FlatBuffers is an efficient cross platform serialization library for C++, C#, C, Go, Java, JavaScript, PHP, and Python. It was originally created at Google for game development and other performance-critical applications.
Currently there is no support for D, so this project would involve building FlatBuffers support from scratch. The goal of the project is to contribute the D support to the upstream repository.
Regarding Protocol Buffers, existing work has been done to provide support for D, however, there are a number of areas that can be improved including:
- comments and deprecated fields handling
- generate interfaces for protobuf services
- benchmarking
Available version
- from HuntLabs github repo huntlabs/google-flatbuffers.
Its Good To Know
It would be worthwhile to have experience working with either Protocol Buffers or FlatBuffers in another language, but such experience is hardly a necessity.
Proposed Project Mentors: Dragos Carp
Lowerer
Project Description
This tool would "translate" compilable D code to compilable D code. See initial idea discussed in Issue 5051. It would offer a variety of lowering services for purposes of tooling, debugging, and project management:
- do not output function bodies, .di style
- write deduced attributes for functions (useful when function bodies are not written)
- expand all possible mixins in the code
- execute lookup on all symbols and write the full symbol, e.g. writeln becomes .std.stdio.writeln
- explicitate all user-defined operators, e.g. a + b becomes a.opBinary!"+"(b)
- replace all wholesale imports with detailed imports that specify the symbols needed
- write specialized versions for all templates used within the module (this is likely to be tricky)
- lower all scope statements into try statements
- lower all foreach statements into for statements
- specify the exact symbols needed for each import statement (which means: if no symbols, the import is redundant - easy to mark as a warning by a subsequent tool)
- evaluate all static ifs possible
- lower code using version(), i.e. make the unused branch disappear
- make all comments disappear
- make only non-documentation comments disappear
- evaluate all possible CTFEs (tricky)
- introduce named values instead of temporaries wherever order of evaluations is defined.
Proposed Project Mentors: TBD
fork()-based Garbage Collector
Project Description
Gustavo Rodriguez-Rivera and Vincent Russo authored a paper on an interesting take on a garbage collector: leverage efficient fork() implementations, which in many Unix systems take advantage of hardware-provided copy-on-write semantics for duplicated memory pages across processes.
This idea is already leveraged in the high-performance garbage collector for D implemented and used by Sociomantic. (A lingering issue is fork() and malloc() share a lock, which is problematic.) Leandro Lucarella, the engineer who wrote the implementation, has open sourced it here, but that is a bitrotten version that has fallen on the wayside.
Leandro would be glad to assist with questions by a motivated implementer. Gustavo has quite a few ideas for improvements, including a possible Windows implementation, and may be able to even coauthor a paper.
Proposed Project Mentors: TBD
Linux debugger
Project Description
ZeroBUGS is a high-quality, source-level debugger for Linux implemented from first principles in C++ by Cristian Vlasceanu. The author got busy with work and the project has since bitrotten, as did a fork of it by a different engineer.
ZeroBUGS presents amazing opportunities for D/Linux debugging, and Cristian is willing to guide a motivated implementer.
Who's (Using) Who?
Project Description
It happens often that executables include code that seems unused (e.g. a typical "hello world" links in functions that are not easily explained). A tool that shows dependency chains would be a great helper in understanding what dependencies are at work, and would give insight into how to reduce them.
The tool would output for each function all symbols it uses. The tool's output would be in one (or more) popular format of stock tools for graph drawing, such as DOT, Graphviz, Sage, PGF/TikZ, newGRAPH, etc.
This can be done using Valgrind's plugin, Callgrind, as explained here.
Proposed Project Mentors: Stefan Rohe
Phobos: D Standard Library
There are tonnes of opportunities to contribute to improving D's standard library, Phobos. Here we list some modules that might make good projects:
std.benchmark
Ideally every function in Phobos should have its own benchmark suite which is run for every PR to check for performance improvements or regressions.
- Additionally support for the new big O annotation here would be nice.
- Existing work: here, and here, and here (QuickText-like testing).
std.i18n
Design and implement a basic internationalization framework. It may be possible to implement this with pragma(msg). For proof of concept see http://arsdnet.net/dcode/i18n.d . It should provide at least the following functionality:
- A locale part, std.i18n.locale which should detect a user's default lanaguage, select a global application lanaguage, and provide types to describe and work with locales.
- A text translation part, std.i18n.translation, which should be gettext compatible, preferably using the gettext serialized hashtables in .mo files, and provide low level (gettext like) and high level (boost::locale like) APIs.
- A tool to extract strings which need to be translated from D code. This should preferably be based on DScanner but alternately could use regular expressions. Optionally support for D code could be added to xgettext.
std.parallelism
std.parallelism needs a review and some benchmarking - prior to making improvements. As part of this is would be good to have a standard benchmarking framework, hence the idea of std.benchmark. However there is no need for it to be in std (and hence Phobos) in the first instance. So the project(s) would be to create a comparative benchmarking framework that can then be used to analyse std.parallelism on a more scientific basis than has been done to date.
std.units
Unit conversion library
std.serialization
A flexible (de)serialization framework that can be used as a standardized building block for various serialization related things: std.json, std.csv, Protocol Buffers, Cap'n Proto, vibe.d... One important goal would be to define how a user-specified type has to work in order to make it serializable, as well as to allow the end-user (e.g. a user of std.json) to change the serialization of third-party types that cannot themselves be modified. A good starting point is would be to work with the Orange framework.
std.container
- support for custom allocator (aka no GC)
- thread-safe
- performance
- existing work: here and here.
- Additionally lock-free data structures (e.g. based on Martin Nowak's work would be a huge benefit.
std.database
- Provide a general database interface for D
- Replace etc.c.sqlite with a native implementation
- Existing work: here, here, and here
- See also the following DConf talk and this one and this one.
std.encoding
std.encoding needs a complete overhaul. Other encoding packages as ascii, base64, utf8 could be included and a common API should unite them.
std.eventloop
High-performance native event loop abstraction for D.
Existing work:
Phobos inclusion will require that the event loop abstraction is not baked into a specific purpose as that comes later. The specific events, sources and consumers must be configurable and high performant. Existing solution that is well tested in this manner is glib's event loop. The closest to this design in D would be SPEW.
For this work to succeed the following things must be in Phobos:
- The abstraction
- An example implementation of the event loop
Available in the community:
- Sockets support
- Windowing support
To simplify matters only Windows support needs to be included for the example sources and consumers of events.
This work would allow D to have a high performance (and correctly performing) windowing, timers and sockets libraries that can integrate should the sources be cross supported.
The biggest domain limitation to this work would be threading. The event loop library should be aware that some sources and consumers may be required to be thread only, global only, or both.
std.graph
Graphs are used in all sorts of contexts - from low-level network communication to high-level data science. At the moment there is only one unmaintained D library, but Boost::graph would be a good direction.
Proposed Project Mentors: TBD
DUB: D's package manager
Project Description
DUB - D's package manager - is one of the central infrastructure tools in the D world as a convenient build and package management tool for the D community. With D gaining more and more popularity, it's also a key tool to guarantee D's further adoption. Thus there are many great ideas to improve DUB:
- separate compilation and caching
- extensibility through DUB
- control flow directives
- build system support for C/C++
- git support
- support dub install for distributions
- support building a {snap, Debian, Arch, ...} package out of DUB package
Proposed Project Mentors: TBD
Propose your own project
Project Description
Do you have your own vision for improving D's success? That's great! Are you convinced that your project helps to advance open source technology related to the D programming language? Then simply get in touch with D's GSoC org admin (Craig) and potential mentors for your project.
If you are searching for inspiration, you might want to have a look at the list of D Improvement Proposals (DIPs), the high-level vision for this semester or the wish list.
Ideas From Previous Years
GSoC idea pages from past years:
- GSoC 2017 Ideas (not accepted)
- GSoC 2016 Ideas (accepted, 4 slots)
- GSoC 2015 Ideas (not accepted)
- GSoC 2014 Ideas (not accepted)
- GSoC 2013 Ideas (not accepted)
- GSoC 2012 Ideas
- GSoC 2011 Ideas
Tips for students
Please see the "gsoc" articles at our official blog which contain experience reports from students of previous years.
Daniel Pocock has written a detailed blog about initiatives students can take if they want to have a serious chance of being selected in GSoC without a focus on one specific organization.
To learn more about potential mentors check our mentor page here.
Tips for Mentors
If you are interested in mentoring, please check out the organization administrator and mentor manual for more information.