Computing Systems are evolving towards more complex, hetero-geneous systems where multiple computing cores and accelerators on the same system concur to improve computing resources utili-zation, resources re-use and the efficiency of data sharing across workloads. Such complex systems require equally complex tools and models to design and engineer them so that their use-case requirements can be satisfied. Adaptive Traffic Profiles (ATP) introduce a fast prototyping technology, which allows one to model the dynamic memory behavior of computer system devices when executing their workloads. ATP defines a standard file format and comes with an open source transaction generator en-gine written in C++. Both ATP files and the engine are portable and pluggable to different host platforms, to allow workloads to be assessed with various models at different levels of abstraction. We present here the ATP technology developed at Arm and pub-lished in [5]. We present a case-study involving the usage of ATP, namely the analysis of the worst-case latency at a DRAM control-ler, which is assessed via two separate toolchains, both using traf-fic modelling encoded in ATP.

Heterogeneous systems modelling with Adaptive Traffic Profiles and its application to worst-case analysis of a DRAM controller

Matteo Andreozzi;Giovanni Stea;
2020-01-01

Abstract

Computing Systems are evolving towards more complex, hetero-geneous systems where multiple computing cores and accelerators on the same system concur to improve computing resources utili-zation, resources re-use and the efficiency of data sharing across workloads. Such complex systems require equally complex tools and models to design and engineer them so that their use-case requirements can be satisfied. Adaptive Traffic Profiles (ATP) introduce a fast prototyping technology, which allows one to model the dynamic memory behavior of computer system devices when executing their workloads. ATP defines a standard file format and comes with an open source transaction generator en-gine written in C++. Both ATP files and the engine are portable and pluggable to different host platforms, to allow workloads to be assessed with various models at different levels of abstraction. We present here the ATP technology developed at Arm and pub-lished in [5]. We present a case-study involving the usage of ATP, namely the analysis of the worst-case latency at a DRAM control-ler, which is assessed via two separate toolchains, both using traf-fic modelling encoded in ATP.
2020
978-1-7281-7303-0
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1038440
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