Understanding High Performance Computing (HPC): Principles, Architecture, and Performance Metrics

High‑performance computing (HPC) leverages supercomputers and parallel‑processing techniques to finish long‑running tasks quickly or to execute many tasks simultaneously, and the HPC market combines traditional and rapidly emerging segments targeting high‑end users and benchmark projects with a trend toward broader accessibility.

How HPC Works

In HPC, information is processed mainly in two ways: serial processing performed by the central processing unit (CPU), where each core typically handles one task at a time and is essential for operating systems and basic applications; and parallel processing that can use multiple CPUs or graphics processing units (GPUs).

GPUs, originally designed for graphics, can execute many arithmetic operations across data matrices (such as screen pixels) at once, making them well‑suited for parallel workloads in machine‑learning applications like object detection in videos.

Advancing beyond current supercomputing limits requires diverse system architectures. Most HPC systems interconnect multiple processors and memory modules with ultra‑high‑bandwidth links to enable parallel processing, and some combine CPUs and GPUs in heterogeneous computing configurations.

Computing performance is measured in FLOPS (floating‑point operations per second). By early 2019, top‑tier supercomputers could achieve 143.5 petaFLOPS (10¹⁵ FLOPS), while high‑end gaming desktops reach about 200 gigaFLOPS (10⁹ FLOPS), a million‑fold slower. The next milestone, exaFLOPS (10¹⁸ FLOPS), would be roughly 1,000 times faster than the current petaFLOPS class.

FLOPS describe theoretical speed; achieving it requires continuous data transfer to processors, so system design must consider data‑throughput, memory bandwidth, and interconnect latency.

Reaching exaFLOPS performance would roughly require 5 million desktop machines, assuming each provides 200 gigaFLOPS.

Terminology

High‑Performance Computing (HPC): a broad class of powerful computing systems ranging from a single CPU + several GPUs to world‑leading supercomputers.

Supercomputer: the most advanced HPC machines, defined by ever‑increasing performance benchmarks.

Heterogeneous Computing: an architecture that optimizes both serial (CPU) and parallel (GPU) processing capabilities.

Memory: storage within an HPC system that provides fast data access.

Interconnect: the system layer that enables communication among processing nodes, existing at multiple levels in supercomputers.

PetaFLOPS class: systems designed to perform 10¹⁵ floating‑point operations per second.

ExaFLOPS class: systems designed to perform 10¹⁸ floating‑point operations per second.

Why do HPC?

From a system perspective, HPC integrates resources to satisfy growing performance and functionality demands; from an application perspective, it decomposes workloads to enable larger‑scale or finer‑grained computation, addressing scientific and engineering problems through intensive simulation, data processing, and networking.

Report collections (2020‑2021 HPC market summaries, HPC/AI market analyses, solution design and testing standards) are listed for further reading.

Full content download links and purchase information for related e‑books are provided.

Source: 智能计算芯世界.

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