Project Application Guide

Marlowe GPU Project Application – Preparation Guide

Below is a brief guide detailing the information you will need to complete a Medium or Large project application for Marlowe. Please review the following, and take note of the job profile information, storage requirements, and PDF instructions. The application form has more detailed instructions.

Section 1: Project & PI Information
Prepare basic project details including project title, abstract, PI name, group member SUNet IDs, and any urgent timelines (e.g., upcoming grant or conference deadlines).

Section 2: Project PDFs
a) Computational Suitability Statement (CSS): You will need to upload a 2–4 page PDF describing computational needs, readiness, scalability, and justification for using Marlowe. The 2-4 page PDF for medium projects should focus on computational suitability rather than a full scientific narrative, please include:

  • A brief scientific overview for context
  • Prior experience on Marlowe or similar GPU-based systems -
  • Any weak or strong scaling studies (completed or planned) -
  • Codes and toolchains used (include GitHub links, if available, with instructions on how to run your codes) -
  • Job profiles: wall time, GPUs/node, concurrency, memory, I/O, and checkpointing -
  • Computational readiness and tuning status, expected/demonstrated MFU, etc Provide detail on why your workload requires more than standard lab or cloud resources.
    • Large projects (>10,000 GPU-hours) should provide strong evidence of readiness and scalability.


(FOR LARGE PROJECTS ONLY)  b) Research Impact Statement (RIS): You will need to upload a 3–4 page PDF with a detailed description of the science to be peer reviewed and then evaluated by the Marlowe Executive Committee.  Please include:

  • A brief description of the scientific impact of the proposed project
  • How the proposed project fits into your overall computational science program
  • If this research pertains to a grant, please include the abstract and the specific aims of the grant here. If not, please provide a list of aims and describe how access to Marlowe would support the proposed research.

Section 3: Computational Profile
Summarize the typical and max job type, wall time, GPU and node usage, concurrency, and usage pattern for this project. This helps assess fit with system capabilities.

Section 4: Technical Requirements & Feasibility
List software frameworks, container tools, and any special configuration needs.

Section 5: Storage & Data
Estimate scratch storage requirements -- capacity. Indicate how data will be sourced, moved, and stored. Include details on checkpointing (if applicable).

Section 6: Impact & Acknowledgments
Briefly describe expected outcomes such as publications or software.

Review Process

1. Computational Suitability Review for Medium and Large Projects (Staff)
Staff will review the CSS for both Medium and Large projects, considering the following areas:

  • Experience
    Assessment of familiarity with GPU clusters, including past experiences
  • Software and Resource Requirements
    Review of codes, toolchains, clear instructions for running applications, and job profiles for use of GPUs, CPUs, memory, I/O, and checkpointing
  • Computational Readiness
    Evaluation of scaling, optimization, computational efficiency (e.g., MFU), and
  • Need for Marlowe
    Justification for needing GPU resources beyond standard lab or cloud environments, Sherlock, etc.


2. Scientific Review for Large Projects (Domain Experts)
In addition to a CSS Review, for Large project applications, domain experts will also review the RIS for research impact and validity, considering the following areas:

  • Scientific Impact
    Clearly define how the proposed research will advance the scientific field or technological area
  • Validity of the Scientific Approach
    Provide a rationale supporting the likelihood of producing meaningful and impactful results