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GSoC 2020

This is a list of summer projects for OSS incubators and research projects affiliated with CROSS. If you have any questions, please visit our Gitter channel: Join the chat at https://gitter.im/uccross/gsoc

LiveHD

This is a proposal of GSoC projects for LiveHD.

Title Parallel Mockturtle with LiveHD
Mentor(s) Jose Renau
Skills C++
Description Mockturtle is being integrated with LiveHD. The goal of this project is to create a parallel version where each partition is "mockturtled" in parallel. This requires to create a regression testting.
Link https://github.com/masc-ucsc/livehd/blob/master/docs/projects.md#mockturtle-qian-chen
Difficulty high
Title Tree-sitter Pyrope
Mentor(s) Jose Renau
Skills Javascript
Description Tree-sitter allows incremental parsers. Pyrope is the in-house HDL. We have a javascript (pegjs) Pyrope grammar, the goal is to have an equivalent tree-sitter that also incrementally update CFGs.
Link https://github.com/masc-ucsc/livehd/blob/master/docs/projects.md#tree-sitter-pyrope
Difficulty high
Title Liberty with LiveHD
Mentor(s) Jose Renau
Skills C++
Description Liberty is the de-facto standard to specify ASIC/FPGA libraries. The goal is to parse a liberty file and populate LiveHD/LGraph nodes.
Link https://github.com/masc-ucsc/livehd/blob/master/docs/projects.md#liberty
Difficulty Medium
Title Pyrope Format
Mentor(s) Jose Renau
Skills C++
Description Improve the Pyrope code generation with LNAST to support alignment, comments
Link https://github.com/masc-ucsc/livehd/tree/master/inou/cgen
Difficulty Medium

Popper is a workflow execution engine based on Github actions. This is a list of ideas for projects related to Popper:

Title Example Workflows
Mentor(s) Ivo Jimenez
Skills Bash, Python, C++ (optional), Rust (optional)
Description

One or more the following (time permitting):

Link See repos in https://github.com/popperized
Difficulty High
Title Add support for additional container engines
Mentor(s) Ivo Jimenez
Skills Python (strong), Go (basic), Bash (basic)
Description Add support for executing workflows in one or more of the followin (time permitting): Podman, LXD, Vagga, Charliecloud, SciUnit.
Link https://github.com/systemslab/popper
Difficulty Medium
Title Transparently run workflows in a Kubernetes cluster.
Mentor(s) Ivo Jimenez
Skills Python (strong), Go (basic), Kubernetes (basic)
Description Given a kubeconfig file, allow Popper users to execute a workflow in a kubernetes cluster. This involves implementing a module that resembles a container engine (popper run --engine kubernetes), with the difference that containers are deployed in the cluster.
Link https://github.com/systemslab/popper
Difficulty High
Title Workflow Viewer and Editor
Mentor(s) Ivo Jimenez
Skills GUI development (strong), Javascript (strong)
Description Create a javascript-based viewer of Popper pipelines that allows users to visually explore a pipeline and its contents, similar to Github's built-in (see live example here) workflow editor. As part of this project, action and workflows catalogs will also be implemented, allowing users to search from an existing list of workflows and actions.
Link https://github.com/blkswanio/blackswan
Difficulty Medium

The Skyhook Data Management project extends object storage in the cloud with data management functionality. Skyhook enables storing and query database tables in Ceph distributed object storage, and supports multiple data formats including Google Flatbuffers and Apache Arrow as well as text and scientific file formats. Skyhook partitions and formats data as objects, and we utilize Ceph's object class extension mechanism to develop custom read/write and processing methods that can be executed directly within storage.

Title Compaction of formatted database partitions within objects
Mentor(s) Jeff LeFevre
Skills C++
Description This project will develop object class methods that will merge (or conversely split) formatted data partitions within an object. Self-contained partitions are written (appended) to objects and over time objects may contain a sequence of independent formatted data structures. A compaction request will invoke this method that will iterate over the data structures, combining (or splitting) them into a single larger data structure representing the complete data partition. In essences, this methods will perform a read-modify-write operation on an object's local data.
Link https://github.com/uccross/skyhookdm-ceph/issues/33
Difficulty high
Title Database statistics collection on partitioned data
Mentor(s) Jeff LeFevre
Skills C++
Description This project will develop object-class methods to compute data statistics (histograms) for each object and store them in a query-able format within each storage server’s local RocksDB, then write client code to accumulate all the object-local statistics into global statistics for a given database table.
Link https://github.com/uccross/skyhookdm-ceph/issues/77
Difficulty high
Title Extend current aggregations to include sort/groupby for database partitions
Mentor(s) Jeff LeFevre
Skills C++
Description We have developed methods (C++) for data management including data processing and indexing. This project will develop object-class methods methods to sort/group query result sets. This requires extending the current code (select/project/basic-aggregations - min/max/sum/count) to support groupby and/or orderby.
Link https://github.com/uccross/skyhookdm-ceph/issues/23
Difficulty medium

Inconsistent relational databases are the ones that violate one or more integrity constraints defined over their schema. We are developing CAvSAT, which aims to be a scalable and comprehensive system for query answering over inconsistent databases.

Title CAvSAT (Consistent Answers via Satisfiability Solving)
Mentors Akhil Dixit, Phokion G. Kolaitis
Skills Java and SQL (required), Node.js and React (optional)
Description In general, computing consistent answers over inconsistent databases is an intractable problem. However, for certain classes of SQL queries and integrity constraints, there is an efficient algorithm to compute consistent answers. The first task of this project is to make the student familiar with the literature and implement this algorithm. Second, the student will conduct experiments with both synthetic and real-world datasets, to compare the performance of this algorithm with other methods. If the student is interested in front-end or full-stack development, they may work on developing some of CAvSAT's user interface components using technologies such as React and write code that connects to CAvSAT's backend via RESTful APIs.
Papers for Reference https://dl.acm.org/doi/10.1145/3299869.3300095, https://link.springer.com/chapter/10.1007/978-3-030-24258-9_8, https://dl.acm.org/doi/10.1145/303976.303983, https://dl.acm.org/doi/10.1145/3068334
Project Link https://github.com/uccross/cavsat
Difficulty Medium