Software & Apps

Showing 1 - 19 results of 19

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: a versatile tool to manage Weather and Climate Experiments in diverse Supercomputing Environments.

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.

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

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:

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.

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.

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

The PMES Framework allows users to execute jobs in the cloud.

pyDock is a fast protocol which uses electrostatics and desolvation energy to score docking poses generated with FFT-based algorithms.

Saiph is a Domain Specific Language developed at BSC for simulating physical phenomena modeled by Partial Differential Equations systems designed for users  that are not experts in numerical methods neither programming for supercomputers

servIoTicy is a scalable IoT stream processing platform. It provides multi-tenant data stream processing capabilities, a REST API, data analytics, advanced queries and multi-protocol support in a combination of advanced data-centric services.

Energy Aware Runtime (EAR) offers an automatic, dynamic and transparent solution to energy aware users with minimal performance overhead. EAR  dynamically detects the iterative pattern of an HPC application while it’s running (through Dynamic Pattern Detection - DPD). Once the application structure is detected, it monitors the application and computes the application signature (CPI,GBs,Time and Power) and selects the optimal node frequency based on user-guided energy policies to quantify the trade-off between power, performance and energy. These policies use performance models that receive as input the application signature, computed at runtime,  and the architecture characterization done at installation time.

Volcanic ash dispersal modelling

Pandora is a framework designed to create, execute and analyse agent-based models in high-performance computing environments. It has been programmed to allow the execution of large-scale agent-based simulations, and it is capable of dealing with thousands of agents developing complex actions. The users can choose to develop their code in Python (for fast prototyping) or C++ (complex models). Interfaces of both versions are identical, and share the same C++ base code (assuring compatibility and efficiency).

s2dverification (seasonal to decadal verification) is an R framework that aids in the analysis of forecasts from the data retrieval stage, through computation of statistics and skill scores against observations, to visualisation of data and results. While some of its components are only targeted to verification of seasonal to decadal climate forecasts, it provides tools that can be useful for verification of forecasts in any field.

Find out more in the overview below, on the wiki page or on the CRAN website.
You can also sign up to the s2dverification mailing list by sending a message with the subject "subscribe" to if you want to keep abreast of internal discussons or latest development releases.

Tiramisu is a data analytics tool for processing, transforming and exploiting data embeddings obtained through deep learning models.