H

high-performance computing

The NAStJA framework provides an easy way to enable massively parallel simulations for a wide range of multi-physics applications based on stencil algorithms.

Python API and CLI for remote submission and monitoring of Python applications on HPC.

An application that requires significant computation to be resilient is an essential feature, and dealing with faults is critical to running an application in some high-performance computing environments. The Dependability Library for Iterative Applications (DeLIA) proposed was designed to be applications that use high-performance techniques and have synchronization moments.

Service Discovery and Load Balancer implementation in Rust. Features include service registration, health checks, and load balancing with Prometheus metrics integration. Designed for high-performance microservices architecture.

Standard Template Adaptive Parallel Library: https://parasollab.web.illinois.edu/research/stapl/

SuperConga: Superconductivity simulation framework on GPU.

XStore is a high-performance key-value store for time-series

NeuroML-based neural simulator

Github repository of VerHem project source tree. A tensor-valued (up to 18 components) solving, post-processing and visualization parallel suite for 3D GL equations and complex geometries with adaptive mesh.

An application that requires significant computation to be resilient is an essential feature, and dealing with faults is critical to running an application in some high-performance computing environments. The Dependability Library for Iterative Applications (DeLIA) proposed was designed to be applications that use high-performance techniques and have synchronization moments.

A NAStJA Application