Software & Apps

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The performance tools developed at BSC are an open-source project targeting not only to detect performance problems but to understand the applications' behavior.

EAR software is an energy management framework for HPC including (among other components) the EAR library and EAR Global Manager. EAR library is a dynamic, transparent, and lightweight runtime library that controls the energy consumed by mpi jobs without any application modification or user input. EAR library guarantees the efficient utilization of system energy. It can be configure to boost energy efficient applications or to save energy by reducing the frequency up to a maximum performance degradation (controlled by EAR). EAR dynamically identifies repetitive regions in parallel applications (outer loops) without adding any annotation or user input. The algorithm in charge of detecting these regions is called DynAIS. DynAIS is an innovative multi-level algorithm with very low overhead. EAR internals are DynAIS driven, being able to evaluate EAR decisions, one of the key differences between EAR and other solutions. Thanks to DynAIS, EAR dynamically computes the Application Signature, a very reduced set of metrics that characterize application behaviour (CPI,GBs,Time and Power) . The Application Signature together with the HW characterization (we call it System Signature) are the inputs for the power and performance models used by EAR. EAR proposes a totally distributed frequency selection design avoiding interferences and additional noise in the network or the file system. Apart from EAR library, EAR framework includes the EAR Global Manager (EARGM). This component controls the energy consumed in the system following system configuration. It can be configured to work as a system monitoring tool, reporting warning messages, or it can be configured to be pro-active and automatically adapt system settings being coordinated with EAR library. Since EAR library is aware of application characteristics, it can react to the different EARGM warnings levels based on application characteristics and the energy efficiency measured. The combination of EARGM + EAR library makes EAR a Cluster solution for energy management.

Even though EAR library can be only loaded with MPI jobs, the rest of EAR components (not mentioned for simplicity), are valid for any type of application. Being a real global solution suitable for production systems.

The Energy Aware Runtime software has developed in the framework of the BSC-Lenovo collaboration project

Tool for the estimation of probabilistic WCET based on execution time measurements (in the form of an R script). 

Details of the method available in: https://doi.org/10.1145/3065924

Multi-cores in real-time systems: opportunities and challenges
Multi-core processors are becoming the baseline computing solution in critical embedded systems. While multi-cores allow high software integration levels, hence reducing hardware procurement and SWaP (Space, Weight and Power) costs, their use challenge current practices in timing analysis.