Glossary
What is HPC?: rawcompute.in Glossary
HPC (High-Performance Computing) refers to large-scale compute infrastructure, typically clusters of interconnected servers, used to solve complex computational problems in science, engineering, and AI.
High-Performance Computing (HPC) encompasses the use of supercomputers and compute clusters to perform calculations that are too large or time-sensitive for standard servers. Traditional HPC workloads include weather modelling, computational fluid dynamics (CFD), molecular dynamics simulations, seismic processing, and financial risk modelling. With the rise of deep learning, AI training has become one of the largest HPC workloads, driving demand for GPU-accelerated HPC clusters.
An HPC cluster typically consists of many compute nodes (each with CPUs and/or GPUs) connected by a high-speed, low-latency network fabric (InfiniBand or high-speed Ethernet). A shared parallel file system (Lustre, GPFS, or BeeGFS) provides storage accessible to all nodes. Job schedulers like Slurm, PBS, or Kubernetes allocate resources to user workloads. The TOP500 list ranks the world’s most powerful HPC systems by LINPACK benchmark performance.
Why it matters when buying hardware
If your organisation performs large-scale simulations or AI training across multiple nodes, you are building an HPC cluster. The key design decisions are compute architecture (CPU-only vs GPU-accelerated), interconnect fabric (InfiniBand vs Ethernet), storage architecture (parallel filesystem vs object storage), and software stack (Slurm, container orchestration, monitoring). Rawcompute.in designs and deploys HPC clusters for Indian research institutions, pharmaceutical companies, and AI startups, including the full hardware stack from GPU nodes to networking and storage.