HPCCluster

A high-performance computing (HPC) cluster is a group of computers connected to execute computational tasks in parallel. It typically includes a head node for management, multiple compute nodes for processing, a high-speed interconnect, and a shared storage system. Cluster software provides resource management and user access. Compute nodes often house multiple CPUs and may include accelerators such as GPUs or FPGAs. The head node handles authentication, job submission, and system monitoring.

The interconnect forms the backbone of an HPC cluster. Common choices include InfiniBand, high-speed Ethernet variants, and Omni-Path, with topologies designed to minimize latency and maximize bandwidth. Parallel applications use programming models such as MPI and OpenMP to coordinate work across nodes. Storage is typically a parallel file system (such as Lustre or GPFS) or clustered object stores to support concurrent I/O from many compute processes.

A typical software stack includes an operating system, a job scheduler (for example SLURM, PBS, or Grid Engine), environment modules, and compilers. MPI implementations (OpenMPI, MPICH) enable message passing between processes; accelerators may be targeted with CUDA or HIP. Performance is evaluated using benchmarks that examine strong and weak scaling, as well as peak FLOPS, though real-world performance depends on workload characteristics, network behavior, and I/O patterns.

Use cases encompass scientific simulations, computational chemistry, climate modeling, genomics, and large-scale data analytics. Management focuses on balancing load, maintaining reliability, and controlling power consumption. Clusters can be expanded by adding compute nodes or accelerators, and software portability can be enhanced through virtualization or containerization.