Presentation
Facilitating Bug Detection for OpenMP Offloading Applications
DescriptionThe paper introduces ARBALEST-VEC, a redesigned
dynamic analysis tool for detecting data inconsistencies in
OpenMP offloading applications, specifically targeting GPU
environments. Building upon the shortcomings of its predecessor,
ARBALEST, the new tool incorporates several improvements.
ARBALEST-VEC is implemented on a more recent version of
LLVM, addressing issues such as inaccurate data movement
modeling and insufficient debugging information in ARBALEST.
It introduces a new OpenMP Tool interface (OMPT) event,
device mem, to accurately capture data movements, thus reducing
runtime overhead and enhancing debugging accuracy. The
tool also leverages additional debug information from LLVM
15 to generate more detailed and user-friendly bug reports.
Furthermore, ARBALEST-VEC employs a dedicated shadow
memory and vectorized dynamic analysis using SIMD instructions
to improve the performance and precision of data inconsistency
detection. Evaluations demonstrate that ARBALEST-VEC offers
improved accuracy, usability, and performance over ARBALEST,
with lower time overhead and more predictable memory usage.
dynamic analysis tool for detecting data inconsistencies in
OpenMP offloading applications, specifically targeting GPU
environments. Building upon the shortcomings of its predecessor,
ARBALEST, the new tool incorporates several improvements.
ARBALEST-VEC is implemented on a more recent version of
LLVM, addressing issues such as inaccurate data movement
modeling and insufficient debugging information in ARBALEST.
It introduces a new OpenMP Tool interface (OMPT) event,
device mem, to accurately capture data movements, thus reducing
runtime overhead and enhancing debugging accuracy. The
tool also leverages additional debug information from LLVM
15 to generate more detailed and user-friendly bug reports.
Furthermore, ARBALEST-VEC employs a dedicated shadow
memory and vectorized dynamic analysis using SIMD instructions
to improve the performance and precision of data inconsistency
detection. Evaluations demonstrate that ARBALEST-VEC offers
improved accuracy, usability, and performance over ARBALEST,
with lower time overhead and more predictable memory usage.
