MSST '05 Proceedings of the 22nd IEEE / 13th NASA Goddard Conference on Mass Storage Systems and Technologies
Deconstructing Commodity Storage Clusters
Proceedings of the 32nd annual international symposium on Computer Architecture
Tracefs: A File System to Trace Them All
FAST '04 Proceedings of the 3rd USENIX Conference on File and Storage Technologies
Accurate and efficient replaying of file system traces
FAST'05 Proceedings of the 4th conference on USENIX Conference on File and Storage Technologies - Volume 4
Profiling and tracing dynamic library usage via interposition
USTC'94 Proceedings of the USENIX Summer 1994 Technical Conference on USENIX Summer 1994 Technical Conference - Volume 1
FiST: a language for stackable file systems
ATEC '00 Proceedings of the annual conference on USENIX Annual Technical Conference
Trace: parallel trace replay with approximate causal events
FAST '07 Proceedings of the 5th USENIX conference on File and Storage Technologies
Multi-Layer Event Trace Analysis for Parallel I/O Performance Tuning
ICPP '07 Proceedings of the 2007 International Conference on Parallel Processing
X-trace: a pervasive network tracing framework
NSDI'07 Proceedings of the 4th USENIX conference on Networked systems design & implementation
Understanding and Improving Computational Science Storage Access through Continuous Characterization
ACM Transactions on Storage (TOS)
Extracting flexible, replayable models from large block traces
FAST'12 Proceedings of the 10th USENIX conference on File and Storage Technologies
ACIC: automatic cloud I/O configurator for HPC applications
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
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There is high demand for I/O tracing in High Performance Computing (HPC). It enables in-depth analysis of distributed applications and file system performance tuning. It also aids distributed application debugging. Finally, it facilitates collaboration within and between government, industrial, and academic institutions by enabling the generation of replayable I/O traces, which can be easily distributed and anonymized as necessary to protect confidential or sensitive information. As a response to this demand for tracing tools, various means of I/O trace generation exist. We first survey the I/O Tracing Framework landscape, exploring three popular such frameworks: LANL-Trace [3], Tracefs [1], and//TRACE [2]. We next develop an I/O Tracing Framework taxonomy. The purpose of this taxonomy is to assist I/O Tracing Framework users in formalizing their tracing requirements, and to provide the developers of I/O Tracing Frameworks a language to categorize the functionality and performance of them. The taxonomy categorizes I/O Tracing Framework features such as the type of data captured, trace replayability, and anonymization. The taxonomy also considers elapsed-time overhead and performance overhead. Finally, we provide a case study in the use of our new taxonomy, revisiting all three I/O Tracing Frameworks explored in our survey, to formally classify the features of each.