Software & Apps

ALOJA Big Data Benchmarking platform: includes tools to define and deploy clusters, orchestrate benchmarking, collect and manage results, and analyze them in Web app including Predictive Analytic tools

Alya is a high performance computational mechanics code to solve engineering coupled problems.

Autosubmit is a Python-based workflow manager to create, manage and monitor complex tasks involving different substeps, such as scientific computational experiments. These workflows may involve multiple computing systems for their completion, from HPCs to post-processing clusters or workstations. Autosubmit can orchestrate all the tasks integrating the workflow by managing their dependencies, interfacing with all the platforms involved, and handling eventual errors.

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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.

Barcelona Subsurface Imaging Tools (BSIT) is a software platform, designed and developed to fulfill the geophysical exploration needs for HPC applications.

COMP Superscalar

Big Data

Distributed Computing

Programming Models

COMPSs Download Form

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COMPSs VM Download Form

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3.2

COMP Superscalar (COMPSs) is a framework which aims to ease the development and execution of parallel applications for distributed infrastructures, such as Clusters, Clouds and containerized platforms.

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dataClay is a distributed data store that enables applications to store and access objects in the same format they have in memory, and executes object methods within the data store. These two main features accelerate both the development of applications and their execution.

Stable release: dataClay 3.0 (May 2023)

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dislib is a distributed computing library highly focused on machine learning on top of PyCOMPSs. Inspired by NumPy and scikit-learn, dislib provides various supervised and unsupervised learning algorithms through an easy-to-use API.

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DLB is a library devoted to speedup hybrid parallel applications. And at the same time DLB improves the efficient use of the computational resources inside a computing node.
More information and downloads can be found at: pm.bsc.es/dlb

EAR software is a management framework optimizing the energy and efficiency of a cluster of interconnected nodes. To improve the energy of the cluster, EAR provides energy control, accounting, monitoring and optimization of both the applications running on the cluster and of the overall global cluster.

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Hecuba is a set of tools and interfaces which aims to facilitate programmers with an efficient and easy interaction with non-relational technologies.

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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

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Mercurium is a source-to-source compilation infrastructure aimed at fast prototyping. Current supported languages are C99, C++11 and Fortran 95. Mercurium is mainly used along with the Nanos++ runtime to implement projects for OmpSs and OpenMP but since it is quite extensible it has been used in other projects including (but not limiting to) Cell Superscalar, ACOTES, software transactional memory, vectorization and correctness.

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.

Nanos++ is a runtime designed to serve as runtime support in parallel environments. It is mainly used to support OmpSs, a extension to OpenMP developed at BSC. It also has modules to support OpenMP 3.1.

PARSECSs is a suite of benchmark applications for parallel architectures. PARSECSs expands the original PARSEC suite with task-based implementations using the OmpSs and/or OpenMP 4.0 programming models. The implementation make use of concepts such as task-parallelism and dataflow relations to achieve maximum performance and offer a diverse set of applications from a wide range of domains. It is designed to use broad concepts of task-parallelism in order to make porting to any generic task-based model easy, and offer important insight to the HPC community in regards to the efficiency and programmability of such models.

PETGEM is an HPC python code for the simulation of electromagnetic fields in real 3D CSEM/MT FM that arise in the geophysics context.

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Source Executable Repository Virtual Appliances

PETGEM

The code is supplied in a manner to ease the immediate execution under Linux platforms. User's manual and technical documentation (developer's guide) are provided in the PETGEM v1.0 archive as well.

PETGEM

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