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GSoC 2019

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

Popper

Popper is a workflow execution engine based on Github actions (GHA). Popper workflows are defined in a HCL syntax and behave like GHA workflows.

Title Popper 2.0
Mentor(s) Ivo Jimenez
Skills Python (strong), Github Actions and HCL (familiar), Docker (familiar)
Description The goal of this project is to add new features to the workflow execution engine, which is based on Github actions (GHA). Please look at the project link to see a list of associated issues.
Link https://github.com/systemslab/popper/projects/12
Title Popper Kubernetes Operator
Mentor(s) Ivo Jimenez
Skills Python (strong), Bash (familiar), Docker (familiar), Go (Strong), Kubernetes (familiar)
Description The goal of this project is to create a Kubernetes operator for running Popper workflows.
Link https://github.com/blkswanio/popper-operator/projects/1
Title Actions Library
Mentor(s) Ivo Jimenez
Skills Python (strong), Bash (familiar), Docker (familiar)
Description The goal of this project is to create a catalog of re-usable actions used in the creation of experimentation pipelines. For example: a Zenodo action that downloads a dataset to be consumed by a later stage in a pipeline; a Spack action that installs the software stack required for an exploration. This has a list of endless possibilities.
Link https://github.com/systemslab/popper/projects/11
Title Example Workflows
Mentor(s) Ivo Jimenez
Skills Python (strong), Bash (familiar), Docker (familiar)
Description The goal of this project is to create example workflows that showcase the distinct actions available for experimenters. This pipelines are relevant in multiple domains such as Genomics, Weather Prediction, Computational (Neuro/Math/etc) Science, among many other domains.
Link https://github.com/systemslab/popper/projects/7
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 workflow editor). As part of this project, a stage catalog will also be implemented, that allows users to search for available stages on Github.
Link https://github.com/systemslab/popper/projects/13
Title Add Support for Popper Workflows in REANA
Mentor(s) Ivo Jimenez
Skills Python (strong), Bash (familiar), Docker (familiar), Go (familiar), Kubernetes (familiar)
Description REANA is a platform for running reproducible analysis. REANA currently supports CWL and Yadage workflows. The goal of this project is to add support for Popper workflows by creating a new reana workflow engine.
Link https://gitter.im/falsifiable-us/popper

LGraph

LGraph (https://github.com/masc-ucsc/lgraph) is the open source infrastructure for Synthesis and Simulation being developed by UCSC. The LGraph goal is to have a common LLVM-like format for synthesis and simulation with a focus on being very fast (Live) and compatible across languages.

Title LGraph and FIRRTL Bidirectional Bridge
Mentor(s) Jose Renau (https://users.soe.ucsc.edu/~renau/)
Skills C++
Description FIRRTL (https://github.com/freechipsproject/firrtl) is the also open source infrastructure as "a platform for writing circuit-level transformations.". Both FIRRTL and LGraph share many common goals. Creating a bridge between them allows to leverage features only existing in each one. There are many differences, for example LGraph has ABC synthesis integration and FIRRTL has CHISEL support. The goal of this project is to implement at C++17 import/export for LGraph that handles FIRRTL.
Difficulty medium
Title LGraph LLVM Code Generation
Mentor(s) Jose Renau (https://users.soe.ucsc.edu/~renau/)
Skills C++
Description LGraph can output Verilog through a Yosys bridge. There is a work-in-progress custom Verilog and Pyrope output for LGraph. The goal of this project is to create an LLVM direct output bridge from LGraph to perform fast hardware simulations.
Difficulty medium
Title LGraph AWS Integration
Mentor(s) Jose Renau (https://users.soe.ucsc.edu/~renau/)
Skills C++/Verilog
Description The goal of this project is to setup a flow in AWS F1 instances to use LGraph for synthesis. LGraph can read Verilog and synthesize with ABC designs for Xilinx FPGAs. The end goal is to create an open source alternative to the Vivado flow used by AWS F1 instances. Since the open source tools are still not ready to handle place and route in AWS F1, for this project, the place and route will use Vivado, but the tools will be hidden behind LGraph. Future projects could target to replace these missing pieces while having a working system.
Difficulty high
Title LGraph FPGA NextPnr Integration
Mentor(s) Jose Renau (https://users.soe.ucsc.edu/~renau/)
Skills C++
Description Nextpnr is the new Open-source FPGA flow that targets Lattice and potentially Xilinx devices. The goal is to interface between LGraph and nextpnr. Creating a bidirectional bridge. The goal is to allow to leverage the incremental synthesis in LGraph, and target FPGAS like Lattice ECP5 and iCE40.
Difficulty medium
Title LGraph ASIC RePlace Placement Integration
Mentor(s) Jose Renau (https://users.soe.ucsc.edu/~renau/)
Skills C++
Description RePlAce (https://github.com/abk-openroad/RePlAce) is a recently released placement tool from UCSD. The goal is to integrate LGraph with RePlAce.
Difficulty high

Skyhook: programmable storage for databases

Skyhook extends object storage in the cloud with data management functionality. Skyhook formats database table partitions as Flatbuffers, and stores each partition as an object in Ceph distributed storage. Ceph object classes mechanism allow users to define custom read/write methods for objects. We have developed methods (C++) for data management including data processing and indexing.

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/skyhook-ceph
Difficulty high
Title Extend current processing methods with column-oriented processing via Arrow
Mentor(s) Jeff LeFevre
Skills C++
Description This project will develop object-class methods to transform on-disk Flatbuffer data (row oriented) into Apache Arrow format (col-oriented) in memory, then work toward extending our row-oriented filters and aggregations to column oriented versions using the Arrow APIs.
Link https://github.com/uccross/skyhook-ceph
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/skyhook-ceph
Difficulty medium

CAvSAT

A comprehensive and scalable query answering system over inconsistent databases.

Title CAvSAT (Consistent Answering via Satisfiability)
Mentor(s) Akhil Dixit, Phokion G. Kolaitis
Skills Java, SQL
Description 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 consistent query answering. In general, computing consistent answers over inconsistent databases is an intractable problem. However, for certain classes of queries and integrity constraints, there is an efficient algorithm to compute consistent answers. The goal of this project is two-fold. First is to get familiar with the literature and implement this algorithm. Second, the student will conduct experiments with both synthetic and real-world databases, to compare the performance of this algorithm with other methods.
Link https://github.com/uccross/cavsat
References https://dl.acm.org/citation.cfm?id=2371212, https://dl.acm.org/citation.cfm?id=303983, https://dl.acm.org/citation.cfm?id=3068334
Difficulty Medium
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