What Is HPC?
High Performance Computing (HPC) refers to the use of supercomputers or clusters of computers that perform massive calculations in parallel, connected by high-speed networks, to solve complex problems much faster than a regular computer can.
Why Do We Need HPC?
As science, industry, and AI evolve, many problems exceed the capability of a single machine. Examples include:
- Scientific research: climate modeling, astrophysics simulations, molecular dynamics for drug discovery
- Industrial applications: computational fluid dynamics for cars and airplanes, material design
- Artificial intelligence: large-scale model training, big data analytics, accelerated inference
These workloads often require hundreds of thousands or even millions of CPU/GPU cores working together—something only HPC can provide.
Key Components of HPC
- Compute: High-performance CPUs, GPUs, or specialized accelerators
- Storage: High-throughput parallel file systems (e.g., Lustre, BeeGFS)
- Networking: Low-latency, high-bandwidth interconnects (e.g., InfiniBand, RoCE)
- Software stack: Job schedulers (e.g., Slurm), parallel programming models (MPI, OpenMP, CUDA)
HPC Meets AI
Recently, HPC and AI have been merging into the new trend of AI+HPC. Training large-scale deep learning models relies heavily on HPC’s compute and distributed capabilities, while AI itself is being used to improve HPC scheduling, optimization, and energy efficiency.
Conclusion
HPC is the engine of scientific computing, enabling breakthroughs in research, industry, and AI. From accelerating discoveries to powering intelligent applications, HPC continues to shape the future of technology and human knowledge.