Abstract
In this paper, we present the Quantitative Usage Analysis of Data (QUAD) tool, a sophisticated memory access tracing tool that provides a comprehensive quantitative analysis of memory access patterns of an application with the primary goal of detecting actual data dependencies at function-level. As improvements in processing performance continue to outpace improvements in memory performance, tools to understand memory access behaviors are inevitably vital for optimizing the execution of data-intensive applications on heterogeneous architectures. The tool, first in its kind, is described in detail and the benefit and the qualities of the presented tool are described on a real case study, the x264 benchmarking application.
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Ostadzadeh, S.A., Meeuws, R.J., Galuzzi, C., Bertels, K. (2010). QUAD – A Memory Access Pattern Analyser. In: Sirisuk, P., Morgan, F., El-Ghazawi, T., Amano, H. (eds) Reconfigurable Computing: Architectures, Tools and Applications. ARC 2010. Lecture Notes in Computer Science, vol 5992. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12133-3_25
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DOI: https://doi.org/10.1007/978-3-642-12133-3_25
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