SOFTWARE & HARDWARE

Licensable technology created by BSC

Showing 1 - 20 results of 44

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.

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.

The current technology is an accelerated version of the purely software implementation of the post-quantum security algorithm named Classic McEliece. It is a hardware/software co-design acceleration.

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3.3

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.

Coyote is an execution-driven simulator based on the open source RISC-V standard, built upon two preexisting simulation tools: Spike and Sparta.

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 3.1 (November 2023)

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.

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

The Dynamic Management of Resources Application Programming Interface (DMR API) is conceived to facilitate the programmability of malleable applications automating resource reallocation, process handling, and data distribution. Process malleability is the capability of reconfiguring the number of processes of an application on-the-fly, in other words, during its execution.

DMR API assists users to adopt malleability in their applications using OmpSs-like syntax. In this regard, with OmpSs pragmas data dependencies are defined and applications can turn malleable. DMR API is based on the Message Passing Interface (MPI) programming model, the standard de facto for developing HPC distributed applications. DMR adjusts the process number of the jobs depending on the cluster status in terms of resource availability and quantity of pending jobs.

A library designed to offer the global advantages of process malleability while providing a minimalist MPI-like syntax. The library includes a
series of predefined communication patterns that greatly ease the development of malleable applications. jThe package also includes a modified SLURM implementation.

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.

 

ecoHMEM is a software ecosystem implementing novel and proven methodology to address automatic object-level placement for heterogeneous memory systems equipped with DRAM, HBM, Persistent Memory, etc.

It is a flexible infrastructure that enables easy integration of existing RTL models with the popular full-system gem5 simulator.

Greasy is a tool designed to make easier the deployment of embarrassingly parallel simulations in any environment. It is able to run in parallel a list of different tasks, schedule them and run them using the available resources. It is the perfect tool to use, for example, when your application is a serial program, and you need to run a large number of instances with different parameters. Greasy packs all these separate runs and uses the resources granted to run as many tasks as possible in parallel. As this tasks finish, Greasy will continue starting the tasks that were waiting for resources.

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

Horus 0.2.2

Horus is an innovative multi-platform GUI workflow manager which aids scientists in their computational research. It can serve as a local application on you computer or as a centralized server for collaborative teamwork. Integrated with a 2D infinite canvas, Horus presents itslef as a modular working environment. Its autonomous blocks enable customizable and distributable workflows via an accessible Python API.

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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