.png){kind=icon}
.png){kind=icon}
Return
THAPI: Tracing Heterogeneous APIs
.png){kind=icon}
PRE
AI
DOI：10.1007/978-3-031-99854-6_4.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
As we reach exascale, production High Performance Computing (HPC) systems are increasing in complexity. These systems now comprise multiple heterogeneous computing components (CPUs and GPUs) utilized through diverse, often vendor-specific programming models. As application developers and programming models experts develop higher-level, portable programming models for these systems, debugging and performance optimization requires understanding how multiple programming models stacked on top of each other interact with one another. This paper discusses THAPI (Tracing Heterogeneous APIs), a portable, programming model-centric tracing framework: by capturing comprehensive API call details across layers of the HPC software stack, THAPI enables fine-grained understanding and analysis of how applications interact with programming models and heterogeneous hardware. Leveraging state of the art tracing framework like the Linux Trace Toolkit Next Generation (LTTng) and tracing much more than other tracing toolkits, focused on function names and timestamps, this approach enables us to diagnose performance bottlenecks across the software stack, optimize application behavior, and debug programming model implementation issues.
Keywords:
High-Performance Computing (HPC)
Programming Models
Tracing and Monitoring
Debugging
Journal
E
IF:
0
Papers:
28
Citations:
0