Scheduler activations: effective kernel support for the user-level management of parallelism
SOSP '91 Proceedings of the thirteenth ACM symposium on Operating systems principles
Dynamic instrumentation of threaded applications
Proceedings of the seventh ACM SIGPLAN symposium on Principles and practice of parallel programming
An Asynchronous Parallel Supernodal Algorithm for Sparse Gaussian Elimination
SIAM Journal on Matrix Analysis and Applications
Performance technology for complex parallel and distributed systems
Distributed and parallel systems
Integrating Kernel Activations in a Multithreaded Runtime System on Top of LINUX
IPDPS '00 Proceedings of the 15 IPDPS 2000 Workshops on Parallel and Distributed Processing
Pajé: An Extensible Environment for Visualizing Multi-threaded Programs Executions
Euro-Par '00 Proceedings from the 6th International Euro-Par Conference on Parallel Processing
Euro-Par '02 Proceedings of the 8th International Euro-Par Conference on Parallel Processing
The role of instrumentation and mapping in performance measurement
The role of instrumentation and mapping in performance measurement
Using Dynamic Kernel Instrumentation for Kernel and Application Tuning
International Journal of High Performance Computing Applications
Measuring and characterizing system behavior using kernel-level event logging
ATEC '00 Proceedings of the annual conference on USENIX Annual Technical Conference
Building portable thread schedulers for hierarchical multiprocessors: the bubblesched framework
Euro-Par'07 Proceedings of the 13th international Euro-Par conference on Parallel Processing
Runtime function instrumentation with EZTrace
Euro-Par'12 Proceedings of the 18th international conference on Parallel processing workshops
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Nowadays, observing and understanding the behavior and performance of a multi-threaded application is a nontrivial task, especially within a complex multi-threaded environment such as a multi-level thread scheduler. In this paper, we present a trace toolkit that allows programmers to precisely analyze the behavior of a multi-threaded application. Running an application through this toolkit generates several traces which are merged and analyzed offline. The resulting super-trace contains not only classical information but also detailed informations about thread scheduling at multiple levels.