TY - GEN
T1 - TEE-Perf
T2 - 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2019
AU - Bailleu, Maurice
AU - Dragoti, Donald
AU - Bhatotia, Pramod
AU - Fetzer, Christof
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/6
Y1 - 2019/6
N2 - We introduce TEE-PERF, an architecture-And platform-independent performance measurement tool for trusted execution environments (TEEs). More specifically, TEE-PERF supports method-level profiling for unmodified multithreaded applications, without relying on any architecture-specific hardware features (e.g. Intel VTune Amplifier), or without requiring platform-dependent kernel features (e.g. Linux perf). Moreover, TEE-PERF provides accurate profiling measurements since it traces the entire process execution without employing instruction pointer sampling. Thus, TEE-PERF does not suffer from sampling frequency bias, which can occur with threads scheduled to align to the sampling frequency. We have implemented TEE-P ERF with an easy to use interface, and integrated it with Flame Graphs to visualize the performance bottlenecks. We have evaluated TEE-PERF based on the Phoenix multithreaded benchmark suite and real-world applications (RocksDB, SPDK, etc.), and compared it with Linux perf. Our experimental evaluation shows that TEE-PERF incurs low profiling overheads, while providing accurate profile measurements to identify and optimize the application bottlenecks in the context of TEEs. TEE-PERF is publicly available.
AB - We introduce TEE-PERF, an architecture-And platform-independent performance measurement tool for trusted execution environments (TEEs). More specifically, TEE-PERF supports method-level profiling for unmodified multithreaded applications, without relying on any architecture-specific hardware features (e.g. Intel VTune Amplifier), or without requiring platform-dependent kernel features (e.g. Linux perf). Moreover, TEE-PERF provides accurate profiling measurements since it traces the entire process execution without employing instruction pointer sampling. Thus, TEE-PERF does not suffer from sampling frequency bias, which can occur with threads scheduled to align to the sampling frequency. We have implemented TEE-P ERF with an easy to use interface, and integrated it with Flame Graphs to visualize the performance bottlenecks. We have evaluated TEE-PERF based on the Phoenix multithreaded benchmark suite and real-world applications (RocksDB, SPDK, etc.), and compared it with Linux perf. Our experimental evaluation shows that TEE-PERF incurs low profiling overheads, while providing accurate profile measurements to identify and optimize the application bottlenecks in the context of TEEs. TEE-PERF is publicly available.
KW - SGX
KW - TEE
KW - profiler
KW - tool
UR - http://www.scopus.com/inward/record.url?scp=85072122219&partnerID=8YFLogxK
U2 - 10.1109/DSN.2019.00050
DO - 10.1109/DSN.2019.00050
M3 - Conference contribution
AN - SCOPUS:85072122219
T3 - Proceedings - 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2019
SP - 414
EP - 421
BT - Proceedings - 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 24 June 2019 through 27 June 2019
ER -