What is Exascale Computing?
AI Summary
Exascale computing refers to supercomputing systems capable of performing at least 1 exaFLOPS, i.e., one quintillion (10¹⁸) floating-point operations per second enabling breakthroughs in scientific simulation, AI, and data-intensive modeling beyond what petascale systems allow.
Why Exascale Computing Matters
Once achieved, exascale computing can help humanity simulate and analyze the world in ways that will help solve our most pressing and complex challenges. It can profoundly change how we live and work, such as improving weather forecasting, healthcare, and drug development, and has important applications in areas of physics, genomics, sub-atomic structures and AI:
- Scientific leap: Enables kilometer-scale climate models, real-time earthquake simulations, advanced quantum-mechanical calculations, and exploration of astrophysical phenomena.
- Frontline supercomputers: Systems like Frontier, El Capitan, Aurora (U.S.), and Jupiter (Europe) now operate at exascale performance levels.
- Strategic leadership: Exascale capabilities are central to computational sovereignty, supporting breakthroughs in energy, health, AI, and national infrastructure.
- Structural innovation: Pushing boundaries in hardware efficiency, large-scale software engineering, and parallel computing methodologies.
How Exascale Computing Works
- Hardware scale: Leverages vast arrays of multi-core CPUs and accelerators (GPUs, AI units), integrated via fast fabric interconnects.
- Parallel software ensembles: Applications are partitioned into high-concurrency workloads, orchestrated across millions of threads, powered by libraries and runtimes developed under initiatives like ECP.
- Resilient operation: Designed to handle component failures gracefully (checkpointing, error correction), while optimizing energy and cooling demands.
- Domain-specific integration: Tailored for emergent workloads—AI, simulation, real-time analytics, and scientific computing, enabled by exascale capacity and software stacks.
Key Components & Features
- Performance scale: Tips the performance threshold at ≥1 exaFLOPS, 1,000 times faster than petascale (10¹⁵ FLOPS) systems.
- Floating-point operations metric: Standardized via 64bit double-precision FLOPS, typically measured by the HPLinpack benchmark.
- High-performance infrastructure: Built on massively parallel architectures optimized for energy efficiency, resilience, and data throughput.
- Ecosystem Co-Design (U.S. DOE): Coordinated development of hardware, software, and applications via the Exascale Computing Project (ECP).
- Dual use and global race: Deployed for scientific research, climate modeling, medicine, and materials, not just military or energy. Multiple nations now compete to deploy exascale machines.
How Arm Powers Exascale Computing
Arm Neoverse is leading a revolution in high-performance computing (HPC), delivering technologies that power the world’s fastest supercomputer and enabling HPC in the cloud. Arm gives HPC designers technologies to drive performance in exascale-class CPUs and the design freedom to implement them independently.
FAQs
What defines “exascale computing”?
Systems performing at least 1 exaFLOPS (10¹⁸ double precision FLOPS).
Why is it lost significant?
It enables complex, high-fidelity simulations in science and AI that were previously impossible or impractically slow.
What are current exascale systems?
U.S. systems: Frontier, El Capitan, Aurora; Europe: Jupiter—operational as of late 2025.
What are the key challenges?
Scaling hardware and software efficiently, managing energy and fault tolerance, and evolving programming models.
How is the exascale ecosystem developed?
Through collaborative initiatives like the U.S. Department of Energy’s Exascale Computing Project (ECP), co-designing systems end-to-end.
Relevant Resources
Exascale workloads benefit from the increased performance, energy efficiency, and design flexibility of Arm Neoverse.
Arm Neoverse fundamentally changes the performance equation for hyperscale data centers and cloud computing.
Building the world's fastest supercomputer doesn't mean breaking the power budget, as engineers at Fujitsu and RIKEN proved.
Related Topics
- AI Technology: The set of computational methods, systems, and hardware used to create, deploy, and scale artificial intelligence applications.
- Artificial Intelligence (AI): The broader discipline of building systems that can perform tasks typically requiring human intelligence, such as reasoning, perception, and decision-making.
- Machine Learning: A type of artificial intelligence (AI) that enables computers to learn from data, recognize patterns, and make decisions with minimal human input.