Fall 2018 Call for Proposals

Fall 2018 Call for Proposals


CROSS is seeking proposals for new research and incubator projects to be considered at our next Industrial Advisory Board (IAB) meeting on October 2, 2018. CROSS is interested in funding research projects which in addition to producing high-impact research also open up a plausible path to open-source software that would be widely adopted. CROSS is also interested in funding incubator projects that turn innovative research prototypes into successful open source software projects. CROSS expects to have funding for one to two new projects, starting in Winter 2019. Projects are reviewed twice a year (end of Winter and beginning of Fall) for renewal of funding


Research Projects:

Faculty as well as Ph.D. students who have completed their class work by Fall 2018 are encouraged to propose research projects. Please note that all research projects must include a UCSC faculty member as an advisor. Higher priority will be given to projects which are aligned with topics of interest (see below) and CROSS’s strategic goals. Priority will also be given to research projects advised by junior faculty. Selected projects can receive funding for up to one graduate student researcher position (GSR). Research projects should raise a fundamental research question and open a plausible path to open source software that would be widely adopted. Funding of a research project is intended to foster excellent research, to enable a student to become an open-source software leader, and to support her work until graduation.


Incubator Projects:

Recent PhD graduates (also from other universities) are welcome to propose incubator projects. Selected incubator projects fund one post-doc position. New incubator projects are expected to start out with significant software infrastructure created as part of a PhD project. The proposal should show strong evidence that the open-source software project would meet with great interest by at least one well-established open-source software community.


Projects funded by CROSS are reviewed by the IAB and the Advisory Committee every six months, and continued funding is based on IAB and the Advisory Committee’s assessment that sufficient progress is being made. The project teams are also required to make all source code available under an open source software license agreement and publish their code in the CROSS software repository.


Important Dates
  • Proposal due: August 28, 2018
  • Notification of proposal shortlist: September 14, 2018
  • IAB meeting and proposal presentations: October 2, 2018
  • Funding notifications: October 10, 2018


Proposal Requirements

Project proposals should include:

  • Project Title
  • Background, overview & objectives
  • Expected time needed to meet objectives
  • Expected staffing needs
  • Explanation how project aligns with the strategic interest and overall work of CROSS
  • Brief explanation of the relevant experience / previous work of project lead (and other team members if applicable)
  • Incubator proposals (and research projects hoping to transition into incubator projects) should also include more detail on the project roadmap and exit strategy.
  • Incubator proposals (and research projects hoping to transition into incubator projects) should also include a risk assessment due to dependencies on any organizations other than CROSS.
Application and Selection Process

To propose a new research or incubator project, send your proposal to CROSS Assistant Director Stephanie Lieggi by August 26, 2018. All submitted proposals will undergo an initial review by the members of our Industrial Advisory Board (IAB)  and the CROSS UCSC Advisory Committee. Based on this initial review, the most responsive projects will be shortlisted and applicants will be notified on September 14, 2018.

If a proposal is shortlisted by CROSS for further consideration, the project lead (or designate) will be required to present their proposal at the CROSS IAB meeting on October 2, 2018. After project presentations, members of the IAB will provide recommendations to the CROSS Director, who then makes the final funding decisions in consultation with the UCSC Advisory Committee. Notifications of funding decisions will be provided by October 10, 2018.

Note: All proposals should highlight how the proposal meets CROSS project criteria (see below). The funding from CROSS typically covers the cost of one graduate researcher (for research projects) or post-doc (for incubator projects) per quarter for the duration of the project.
Project Evaluation Criteria




The CROSS IAB, the CROSS Director, and the UCSC Advisory Committee consider the following criteria when evaluating research and incubator projects –

For research projects

  • The project raises a fundamental research question;
  • The project opens a plausible path to open source software that would be widely adopted; and
  • The project’s topic meets strategic objectives of CROSS.

For incubator projects

  • The project starts out with significant software infrastructure that a recent graduate created as part of their Ph.D. project;
  • There is strong evidence of community interest in the effort and that the resulting opensource software prototype would be widely adopted; and
  • The project’s topic meets strategic objectives of CROSS.
Suggested Topics




CROSS considers proposals in a variety of topic areas, including (but not limited to):

  • Storage Systems;
  • Computational Genomics;
  • Data Science;
  • Data Management;
  • Networking & the Internet of Things;
  • Distributed Systems;
  • Computer Architecture;
  • Energy Management; and
  • Machine Learning.

While CROSS takes the preferences of industry members into consideration when choosing to support projects, funding is also available for projects that foster topic diversity and the Center’s long-term strategic interests. If you have questions about whether your project proposal is appropriate for CROSS funding, please contact CROSS Director Carlos Maltzahn.

Also see current list of funded Research and Incubator projects.

Topics of interest are (but not limited to):

  •  In-store Computing
    • Device interface semantics that allow for dynamic host/device associations
    • Device interface semantics that enable data consistency across devices
    • Domain-specific in-store data management and analytics such as genomics
    • Data privacy and access security
    • Data cleaning
    • Searching, data reduction, statistical modeling, transcoding/format conversion
    • In-memory processing models, including a secure method for offloading processing to smart SSDs
  • Programmable Storage Systems (Programmability and Architecture of Storage Systems)
    • Open source API for in-store compute (programmable storage)
    • Open source tools for in-store compute
    • Compilers, libraries, debuggers
    • Tools to decompose applications for parallel processing of dispersed data
    • Leveraging communication between in-store compute devices o Combining in-store computing and external computing
    • Parallelism for machine learning
    • Barriers to adoption of in-store compute
  •  Predictable Performance
    • Adaptable load balancing (especially using machine learning)
    • Networking with predictable performance and performance management
    • Storage maintenance
    • Coordinating system and device low-priority tasks
    • Storage on disk- and Flash-based Zoned Block Devices, and “hybrid” CMR/SMR
  • Non-volatile Memory and Hybrid Memory Hierarchy Architectures
    • Hypervisor / OS architecture for heterogeneous memory
    • Memory disaggregation in the data center for data intensive applications. This will include memory object definition, representation, optimization, compiler support, and application acceleration
    • Self-aware data orchestration – predictive data positioning through intelligence and learning
    • Converging memory and IO using persistent memory – representative applications, key benefits, theory of operation
    • Operating Systems mechanisms to provide efficient/performant and secure access to non-volatile memory
    • Modeling and simulation of modifications to big data applications/SSD design to optimize performance/wear leveling
    • New data management models (e.g. location awareness) for managing massive amounts of data on storage media that includes non-volatile memory
  •  Frameworks for Power-efficient Analysis
    • Software and hardware support for new number formats








Carlos Maltzahn, Director, carlosm@ucsc.edu

Stephanie Lieggi, Assistant Director, slieggi@ucsc.edu