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MeluXina User Documentation
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MeluXina User Documentation
Welcome
MeluXina supercomputer
MeluXina supercomputer
System overview
Detailed architecture
Gaining access
Gaining access
Project access
Allocations and monitoring
Policies
First steps
First steps
Quick start
Connecting
Software environment
Environment Modules
Software installation
Handling jobs
Transferring data
Managing data
Basic Linux
Application examples
Application examples
AOCC
BLIS
Clang
Eigen
FFTW
FFTW.MPI
GCC
GROMACS
Go
HDF5
imkl
intel
intel-compilers
Julia
MCR
mpifileutils
NVHPC
netCDF
OpenBLAS
OpenMPI
Paraview
Python
R
ScaLAPACK
Apptainer
VTune
HPC
HPC
Welcome
Compiling
Debugging
Profiling
HPDA
HPDA
Welcome
Data Science Development Tools
Data Science Development Tools
Jupyter Lab
Jupyter Lab
Run JupyterLab on Linux
Run JupyterLab on Windows
Convert Notebook to Python
TensorBoard
Optimizations
Optimizations
Acceleration with Numba
Acceleration with Numba
Introduction
Monte Carlo Simulation
Acceleration with CUDA
FPGA
FPGA
Welcome
Intel® LLVM SYCL oneAPI DPC++
Intel® LLVM SYCL oneAPI DPC++
What is the Intel® oneAPI DPC++ compiler
Compiling SYCL programs
Developing SYCL programs
Reporting & profiling SYCL programs
Optimizing SYCL programs
Intel® FPGA SDK (OpenCL)
PyOpenCL using Intel® FPGA SDK
Quantum simulation using Intel® FPGA SDK
How To
How To
Use Llama 3 with NVIDIA TensorRT-LLM and Triton Inference Server
Multi-node & Multi-GPU inference with vLLM
Distribute a Resnet50 training with PyTorch over several GPUs
Use VS Code to develop on Meluxina with ease
Use the remote client for connecting to Linaro Forge
Use PyTorch to run the inference of a pre-trained mode
Containerization
Containerization
Introduction to containers
Apptainer
Module Environment for NVIDIA GPU Containers (NGC)
Cloud
Cloud
Introduction
S3 - Data transfer
JupyterLab
JupyterLab
Introduction
Python
Julia
Kubernetes
Kubernetes
Introduction
Resources
Resources
Deployment
Service
Ingress
Slurm Rest API
Keycloak
What's new
FAQ
FPGA computing using the EuroHPC Supercomputer Meluxina
