Workload Profiling
Modern safety-critical systems are comprised of complex applications and equally complex hardware. Understanding the subtle interplay between software and hardware is the way to go to perform informed resource management. In our lab, we are devising techniques to collect, analyze, and leverage fine-grained knowledge on the interaction between applications, processors, and memory resources.
Projects
RT-Bench
An extensible framework that turns popular benchmarks into periodic, real-time workloads.
Application Phase Driven Resource Management
Detecting application phases and re-assigning cache and memory bandwidth as resource needs change.
9 publications in this area
- MemScope: Open-Source Kernel-Level Framework for Heterogeneous Memory Characterization
- RT-Bench: A Long Overdue Update
- Low-overhead Online Assessment of Timely Progress as a System Commodity
- Observing the Invisible: Live Cache Inspection for High-Performance Embedded Systems
- Know your Enemy: Benchmarking and Experimenting with Insight as a Goal
- RT-Bench: An Extensible Benchmark Framework for the Analysis and Management of Real-Time Applications
- Governing with Insights: Towards Profile-driven Cache Management of Black-Box Applications
- E-WarP: a System-wide Framework for Memory Bandwidth Profiling and Management
- Deterministic Memory Abstraction and Supporting Multicore System Architecture