Multi-level Memory-Centric Profiling on ARM Processors with ARM SPE

High-end ARM processors are emerging in data centers and HPC systems, posing as a strong contender to x86 machines. Memory-centric profiling is an important approach for dissecting an application's bottlenecks on memory access and guiding optimizations. Many existing memory profiling tools leve...

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Vydané v:SC24-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis s. 996 - 1005
Hlavní autori: Miksits, Samuel, Shi, Ruimin, Gokhale, Maya, Wahlgren, Jacob, Schieffer, Gabin, Peng, Ivy
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 17.11.2024
Predmet:
Accuracy
ARM SPE
Conferences
Data centers
Hardware
High performance computing
memory profiling
Optimization
precise event sampling
Program processors
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Shrnutí:High-end ARM processors are emerging in data centers and HPC systems, posing as a strong contender to x86 machines. Memory-centric profiling is an important approach for dissecting an application's bottlenecks on memory access and guiding optimizations. Many existing memory profiling tools leverage hardware performance counters and precise event sampling, such as Intel PEBS and AMD IBS, to achieve high accuracy and low overhead. In this work, we present a multi-level memory profiling tool for ARM processors, leveraging Statistical Profiling Extension (SPE). We evaluate the tool using both HPC and Cloud workloads on the ARM Ampere processor. Our results provide the first quantitative assessment of time overhead and sampling accuracy of ARM SPE for memory-centric profiling at different sampling periods and aux buffer sizes.
DOI:10.1109/SCW63240.2024.00139