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Merge branch 'frontPageLayoutFour' of https://github.com/QuillPusher/compiler-research.github.io into frontPageLayoutFour
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‎README.md

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@@ -133,6 +133,32 @@ docker run --rm -v "$PWD:/srv/jekyll" \
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jekyll serve --livereload
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```
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## Guide to Making Changes to the Website
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### Adding a Project to /projects/ directory on the Website
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It is possible to
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- add a new page with a lot of project details (e.g.,
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`\_pages\testproject.md`) and then add the project excerpt to the projects
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directory `_data\projects.yml`, or
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- you can simply add the project excerpt to the projects directory
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`_data\projects.yml` if there aren't enough details available for the project.
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Next, use the `link` attribute in the `projects.yml` file to define the link
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to the detailed project page (if you created this in the previous step).
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The project excerpt should now automatically show up on the '/Projects/' page
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along with the link to the detailed project page.
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To change the layout of the Projects page itself, you can browse to
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`_pages\projects.md` and edit the Liquid code as needed.
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> Please note that the Projects page exists in parallel to the Open Projects
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> page (`_pages\open_projects.md`), and you should add your project details
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> where it makes more sense.
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[installation]: https://jekyllrb.com/docs/installation/windows/
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[RubyInstaller Downloads]: https://rubyinstaller.org/downloads/

‎_data/contributors.yml

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linkedin: ""
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active: 1
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- name: Ioana Ifrim
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info: Research Staff
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photo: Ifrim.jpg
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email: [email protected]
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education: MPhil Advanced Computer Science, University of Cambridge (2018)
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active: 1
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- name: Alexander Penev
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info: Assoc. Prof.
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photo: Penev.png
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email: [email protected]
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active: 1
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################################################################################
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# 2024 #
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################################################################################
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- name: Ioana Ifrim
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info: Research Staff
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photo: Ifrim.jpg
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email: [email protected]
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education: MPhil Advanced Computer Science, University of Cambridge (2018)
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################################################################################
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# 2023 #
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################################################################################

‎_data/projects.yml

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- name: "Xeus-CPP - a Jupyter Kernel for C++"
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description: |
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Xeus-CPP is a product of OAC-1931408 in collaboration with the QuantStack
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company. It is a Jupyter kernel for C++ based on the native implementation
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of the Jupyter protocol xeus. It is supports the Wasm version of Jupyter
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(JupyterLite). It is a generalization of the Xeus-Clang-Repl (a Jupyter
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plugin supporting C++ development based on ClangRepl).
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With Xeus-CPP, you can write and execute C++ code interactively, seeing
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the results immediately. This REPL nature allows you to iterate quickly
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without the overhead of compiling and running separate C++ programs.
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link: |
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https://github.com/compiler-research/xeus-cpp
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- name: "Clang-REPL - an Interactive C++ Interpreter"
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description: |
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Clang-Repl is an interactive C++ interpreter that allows for incremental
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compilation. It supports interactive programming for C++ in a
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read-evaluate-print-loop (REPL) style.
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Clang-Repl is suitable for exploratory programming and in places where
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time to insight is important. Clang-Repl is a project inspired by the work
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in Cling, a LLVM-based C/C++ interpreter developed by the field of high
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energy physics and used by the scientific data analysis framework ROOT.
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Clang-Repl allows to move parts of Cling upstream, making them useful and
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available to a broader audience.
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link: |
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https://clang.llvm.org/docs/ClangRepl.html
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- name: "CppInterOp - a C++ Language Interoperability Layer"
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description: |
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CppInterOp (previously LibInterOp) is a product of OAC-1931408 and exposes
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APIs from Clang and LLVM in a mostly backward compatibe way. The APIs
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support downstream tools that utilize interactive C++ by using the
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compiler as a service. That is, embed Clang and LLVM as a libraries in
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their codebases.
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The APIs are designed to be minimalistic and aid non-trivial tasks such as
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language interoperability on the fly. In such scenarios CppInterOp can be
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used to provide the necessary introspection information to the other side
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helping the language cross talk. The package makes it easy to deploy as it
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ships Clang as a service without any dependencies.
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link: |
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https://github.com/compiler-research/CppInterOp
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- name: "Cling - an Interactive C++ Interpreter"
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description: |
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Cling is an interactive C++ interpreter that operates on top of the Clang and
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LLVM libraries, utilizing LLVM's Just-In-Time (JIT) compiler for fast and
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optimized compilation processes.
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By adopting a read-eval-print-loop (REPL) approach, Cling is helping C++
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development evolve by enabling rapid application development without the need
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for the traditional edit-compile-run-debug cycle, thus facilitating quick
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prototyping and exploration in C++.
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By providing support for advanced C++ features like templates, lambdas, and
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virtual inheritance, Cling empowers developers in exploratory programming with
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interactive, dynamic language interoperability and rapid prototyping.
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link: |
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https://github.com/root-project/cling
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- name: "Clad - an Automatic Differentiation Tool"
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description: |
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Clad is a plugin for the Clang compiler that enables automatic differentiation
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capabilities for C/C++ codebases. It is a valuable tool for developers seeking
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to streamline complex mathematical computations and optimize their codebase
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efficiently.
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Clad facilitates the generation of derivatives, gradients, Hessians, and
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Jacobians (in forward and/or reverse mode), enhancing the efficiency and
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versatility of numerical computations.
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Clad not only supports partial and higher-order derivatives but also
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integrates seamlessly with frameworks like ROOT, providing a comprehensive
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solution for automatic differentiation needs in C++ applications.
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link: |
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https://github.com/vgvassilev/clad
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‎_includes/header.html

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</a>
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</div>
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<ul id="navbar-collapse-1" class="nav navbar-nav ml-auto navbar-collapse collapse">
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<li class="nav-item dropdown">
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<!-- <li class="nav-item dropdown">
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<a href="#" class="nav-link dropdown-toggle" id="dropdown02" data-toggle="dropdown" role="button" aria-haspopup="true" aria-expanded="false">Research</a>
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<ul class="dropdown-menu" aria-labelledby="dropdown02">
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<li class="dropdown-item"> <a class="nav-link" href="/caas">Compiler-As-A-Service</a></li>
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<li class="dropdown-item"> <a class="nav-link" href="/interactive_cpp">Incremental C++</a></li>
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<li class="dropdown-item"> <a class="nav-link" href="/libinterop">Language Interoperability</a></li>
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</ul>
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</li>
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</li>
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<li class="nav-item dropdown">
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<a href="#" class="nav-link dropdown-toggle" id="dropdown02" data-toggle="dropdown" role="button" aria-haspopup="true" aria-expanded="false">Projects</a>
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<ul class="dropdown-menu" aria-labelledby="dropdown02">
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<li class="dropdown-item"> <a class="nav-link" href="https://rawgit.com/root-project/cling/master/www/index.html">Cling</a></li>
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<li class="dropdown-item"> <a class="nav-link" href="/clad">Clad</a></li>
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</ul>
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</li>-->
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<li class="nav-item">
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<a class="nav-link" href="/research">Research</a>
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</li>
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<li class="nav-item">
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<a class="nav-link" href="/projects">Projects</a>
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</li>
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<li class="nav-item dropdown">
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<a href="#" class="nav-link dropdown-toggle" id="dropdown01" data-toggle="dropdown" role="button" aria-haspopup="true" aria-expanded="false">Results</a>

‎_pages/projects.md

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---
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title: "Compiler Research Projects"
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layout: gridlay
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excerpt: "Notable Projects by Compiler Research Group"
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sitemap: false
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permalink: /projects/
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---
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Following are some notable projects.
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{% for project in site.data.projects %}
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<div class="well" style="padding-left: 20px; padding-right: 20px">
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**{{ project.name }}**
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{{ project.description | markdownify }}
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For more details, please browse to this <a href="{{ project.link }}">link to the project</a>
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</div>
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{% endfor %}
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‎_pages/research.md

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---
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title: "Compiler Research Research Areas"
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layout: gridlay
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excerpt: "Research"
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sitemap: false
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permalink: /research/
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---
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Following are the areas of research that Compiler Research Group is focused on:
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#### [Automatic Differentiation ↗]
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Automatic Differentiation (AD) is a useful technique in scientific research
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fields like machine learning and computational physics. AD enables the
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automatic computation of derivatives of functions with high precision and
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efficiency. A notable implementation of AD is the [Clad plugin for the Clang]
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compiler. This integration not only simplifies the process of differentiation
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but also enhances the performance and accuracy of numerical computations in
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scientific applications.
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In scientific research, where intricate mathematical models are prevalent, the
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utilization of AD through tools like the Clad brings a new level of
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sophistication and speed to derivative calculations. By leveraging AD within
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C++ compilers, researchers can focus more on the scientific aspects of their
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work rather than getting bogged down in manual differentiation tasks. This
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automation not only accelerates the development process but also ensures that
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computations are error-free and consistent.
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#### [Compiler-As-A-Service ↗]
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Compiler as a Service (CaaS) is an evolving technology that redefines the
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traditional approach to compilers by providing a service-oriented
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architecture. Instead of treating the compiler as a black box, the CaaS
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approach helps open up the functionality to make it available as APIs. This
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gives developers unprecedented control and insights into the compilation
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process, while being able to use lightweight APIs for simpler workflows and
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diagnostics, helping create sophisticated applications more efficiently.
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Practical applications of CaaS include deeper and interactive program analysis
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and conversion from one programming language to another (e.g., C++ and
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Python).
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#### [Incremental C++ ↗]
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Despite its high performance capabilities, C++ is not the first programming
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language that comes to mind for rapidly developing robust applications, mainly
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due to the long edit-compile-run cycles.
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Ongoing research in projects such as [Cling], [Clang-REPL], etc. aims to
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provide practically usable interactive capabilities to the C++ programming
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language. The goal is to enable dynamic interoperability, rapid prototyping,
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and exploratory programming, which are essential for data science and other
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scientific applications.
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Following are some practical applications of a "C++ Interpreter," so to speak:
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- In Data Science: Interactive probing of data and interfaces, making complex
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libraries and data more accessible to users.
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- In CUDA: The Cling CUDA extension brings the workflows of [Interactive C++] to
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GPUs without losing performance and compatibility to existing software.
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- In Exploratory Programming: rapid reproduction of results, which is crucial
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during the exploratory phase of a project.
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- In Jupyter Notebooks: Interactive C++ can be [integrated with Jupyter
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Notebooks], providing a swift prototyping and learning experience for C++
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users.
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#### [Language Interoperability ↗]
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Language interoperability helps programmers get the best of both worlds, with
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the ability to work with a high-performance language (e.g., C++), and at the
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same time, take advantage of a more interactive one (e.g., Python), while
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helping them identify each other's entities (like variables and classes) for
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seamless integration.
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This interoperability can be achieved by libraries like [CppInterOp], which
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expose APIs from compilers like Clang in a backward-compatible manner. By
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enabling interactive C++ usage through the Compiler-As-A-Service, CppInterOp
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simplifies complex tasks such as "language interoperability on the fly".
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The practical implications of language interoperability include the growing
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need for systems in data science to be able to interoperate with C++
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codebases. By providing automatic creation of bindings on demand, tools
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like CppInterOp enable Python to interoperate with C++ code dynamically,
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instantiate templates, and execute them efficiently. This dynamic approach not
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only improves performance but also simplifies code development and debugging
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processes, offering a more efficient alternative to static binding methods.
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[Automatic Differentiation ↗]: https://www.open-std.org/jtc1/sc22/wg21/docs/papers/2020/p2072r0.pdf
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[Interactive C++]: https://blog.llvm.org/posts/2020-12-21-interactive-cpp-for-data-science/
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[integrated with Jupyter Notebooks]: https://blog.jupyter.org/interactive-workflows-for-c-with-jupyter-fe9b54227d92
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[CppInterOp]: https://github.com/compiler-research/CppInterOp/blob/main/README.md
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[Clad plugin for the Clang]: https://compiler-research.org/clad/
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[Language Interoperability ↗]: https://cppinterop.readthedocs.io/en/latest/index.html
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[Cling]: https://rawgit.com/root-project/cling/master/www/index.html
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[Clang-REPL]: https://clang.llvm.org/docs/ClangRepl.html
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[Compiler-As-A-Service ↗]: https://compiler-research.org/caas/
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[Incremental C++ ↗]: https://compiler-research.org/interactive_cpp

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