This $154,959 Project Grant awarded by the National Science Foundation (NSF) Integrative Activities (IA) program will fund research to develop efficient and intelligent Unified Memory (UM) design techniques for GPU-accelerated systems. The project, titled "COLLABORATIVE RESEARCH: SHF: SMALL: ACCESS PATTERNS IN MASSIVE PARALLELISM: ABSTRACTIONS AND ORIENTED UNIFIED MEMORY MANAGEMENT FOR GPU ACCELERATED SYSTEMS", aims to address the challenges of managing data migration between host and GPU memories, which is critical for advancing large-scale scientific and deep learning workloads. The key innovation is the "Access Pattern Oriented" (ACCORD) framework, which will enable quantitative assessment of access patterns and their interaction with UM techniques to optimize data movement. The research objectives include devising access pattern abstractions, developing cost analysis methods, designing access pattern-oriented UM techniques, and integrating the ACCORD framework into real-world UM systems. This 3-year project, awarded on June 15, 2024, will be conducted by Clemson University's Division of Research.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $155.0k | 6/14/24 |