High Performance Computing Market Size and Share

High Performance Computing Market Analysis by Mordor Intelligence
The high performance computing market currently stands at a high performance computing market size of USD 60.12 billion in 2026 and is projected to reach USD 87.50 billion by 2031, expanding at a 7.79% CAGR during 2026-2031. This trajectory is fueled by sovereign artificial-intelligence mandates in Asia, record federal appropriations for exascale programs in the United States and an accelerating pivot toward simulation-driven product design across automotive, life-sciences and energy workflows. Persistent supply shortages of high-bandwidth memory and the migration of inference workloads from general-purpose GPUs to custom accelerators also reshape server configurations, encouraging enterprises to adopt modular liquid-cooling and chiplet architectures that extend system lifetimes. Government customers are moving from capability experiments to mission-critical operations, evidenced by the 2024 commissioning of the 2-exaflop El Capitan system for nuclear-stockpile stewardship, while private-sector buyers are tapping cloud burst capacity to handle episodic peaks in computational fluid dynamics and Monte Carlo risk calculus. In parallel, the EURO-NCAP 2030 virtual-testing mandate forces European automotive original-equipment manufacturers to triple simulation throughput, indirectly intensifying GPU demand that already outstrips supply. Against this backdrop, Asia Pacific-based contract research organizations leverage lower energy tariffs and sovereign subsidies to win pharma outsourcing work from North American peers, demonstrating that geography-specific cost structures now modulate workload placement.
Key Report Takeaways
- By component, hardware retained a 51.54% share of the high performance computing (HPC) market in 2025, whereas services are advancing at a 9.42% CAGR through 2031, the fastest rate among all components.
- By deployment mode, cloud installations controlled 48.88% of the HPC market in 2025, while hybrid architectures are forecast to record an 8.22% CAGR to 2031.
- By chip type, GPU-based systems secured 59.22% of 2025 revenue, yet application-specific integrated circuits and AI accelerators are projected to expand at an 8.86% CAGR, the segment’s highest growth pace.
- By industrial application, government and defense workloads led with 24.16% of the HPC market share in 2025, whereas life sciences are poised to grow at a 9.54% CAGR, the fastest among current use cases.
- By geography, North America captured 40.48% of revenue in 2025; however, Asia Pacific is the fastest-rising region with a 7.98% CAGR expected through 2031.
Note: Market size and forecast figures in this report are generated using Mordor Intelligence’s proprietary estimation framework, updated with the latest available data and insights as of January 2026.
Global High Performance Computing Market Trends and Insights
Drivers Impact Analysis
| Driver | (~) % Impact on CAGR Forecast | Geographic Relevance | Impact Timeline |
|---|---|---|---|
| Explosion of AI and ML training workloads in U.S. federal labs and tier-1 cloud providers | +2.1% | North America, with spillover to Europe and Asia Pacific hyperscale regions | Medium term (2-4 years) |
| Surging demand for GPU-accelerated molecular dynamics in Asian pharma outsourcing hubs | +1.3% | Asia Pacific core (China, India, South Korea), expanding to Southeast Asia | Short term (≤ 2 years) |
| Mandatory automotive ADAS simulation compliance in EU EURO-NCAP 2030 roadmap | +1.5% | Europe (Germany, France, Italy), with adoption in North America and Japan | Long term (≥ 4 years) |
| National exascale initiatives driving indigenous processor adoption in China and India | +1.2% | Asia Pacific (China, India), with limited technology transfer to Middle East | Long term (≥ 4 years) |
| Rapid adoption of digital twins for grid-scale battery storage optimization | +0.9% | Global, with early concentration in California, Texas, Germany, Australia | Medium term (2-4 years) |
| Emergence of quantum-inspired annealing accelerators for portfolio optimization | +0.6% | North America and Europe financial hubs (New York, London, Singapore) | Long term (≥ 4 years) |
| Source: Mordor Intelligence | |||
The Explosion of AI and ML Training Workloads in U.S. Federal Labs and Tier-1 Cloud Providers
Federal agencies now embed petaflop-scale infrastructure into operational AI pipelines rather than isolated research sandboxes. Oak Ridge National Laboratory’s 1.2-exaflop Frontier trains foundation models that compress battery-chemistry discovery cycles from 18 months to 6 weeks, validating the transition from exploratory benchmarks to real-world deliverables.[1]Frontier Supercomputer Debuts as World's Fastest, Oak Ridge National Laboratory, ornl.gov The National Science Foundation’s 2025 Genesis Mission earmarks USD 800 million for distributed AI clusters across 20 universities, multiplying regional access to high performance computing market resources. Microsoft Azure’s ND H100 v5 instances provide 3.2-terabit-per-second InfiniBand fabrics that let pharmaceutical firms build 100-billion-parameter transformers without cross-region sharding. The combined federal-private stimulus advances GPU refresh cycles, rendering legacy A100 nodes economically obsolete for trillion-parameter workloads and tightening demand for scarce HBM3e-based accelerators.
Surging Demand for GPU-Accelerated Molecular Dynamics in Asian Pharma Outsourcing Hubs
Contract research organizations in China and India deploy thousands of GPUs to compress small-molecule binding simulations from weeks to hours, leveling the playing field against Western pharmaceutical incumbents. WuXi AppTec’s 5,000-GPU Shanghai cluster screens 10 million compounds per quarter at 40-times CPU throughput, delivering cost per GPU-hour roughly 60% lower than North American labs thanks to subsidized electricity and tax holidays.[2]Business Healthcare and Pharmaceuticals, Reuters, reuters.com India’s PARAM Rudra allocates one-third of its 2025 compute budget to Council of Scientific and Industrial Research laboratories, accelerating tuberculosis drug discovery by fusing AlphaFold-generated protein structures with GPU-driven docking engines.[3]MeitY National Supercomputing Mission, Government of India, meity.gov.in This geographic arbitrage shifts pharmaceutical preclinical pipelines eastward, reinforcing Asia Pacific’s long-run share of the high performance computing market.
Mandatory Automotive ADAS Simulation Compliance in EU EURO-NCAP 2030 Roadmap
Virtual testing now underpins five-star safety ratings across Europe, obligating automakers to model 10 billion digital kilometers before physical prototypes crash into concrete walls. Volkswagen committed to 500 petaflops of new capacity by 2027 and Stellantis earmarked EUR 300 million (USD 339 million) for a Turin simulation hub fed by 4 million connected-vehicle telematics streams. GPU-rich clusters capable of rendering sensor-fusion scenarios at 1,000 frames-per-second replace multi-million-dollar crash labs, producing an immovable layer of compute demand regardless of cyclic vehicle sales. The roadmap also propagates to U.S. and Japanese subsidiaries, widening the addressable high performance computing market horizon.
National Exascale Initiatives Driving Indigenous Processor Adoption in China and India
Export-control friction accelerated domestic silicon programs. China’s 1.3-exaflop Sunway Oceanlight relies on SW26010-Pro processors fabbed at 14 nanometers, sidestepping foreign licensing while supporting climate and aerospace research at scale. India’s 64-core ARM-based AUM processor anchors the forthcoming PARAM Siddhi-AI system to be commissioned in 2026 and confers supply-chain sovereignty for defense use cases. Although single-thread performance lags Western CPUs, massive core counts confer competitively high throughput per watt. These systems divide the global high performance computing market along geopolitical axes, with Western vendors competing on performance and Asian suppliers on autonomy.
Restraints Impact Analysis
| Restraint | (~) % Impact on CAGR Forecast | Geographic Relevance | Impact Timeline |
|---|---|---|---|
| Escalating datacenter water-usage restrictions in drought-prone U.S. states | -0.8% | Western United States (California, Arizona, Nevada), with emerging constraints in Texas | Short term (≤ 2 years) |
| Ultra-low-latency edge requirements undermining centralized cloud economics | -0.6% | Global, with acute impact in autonomous vehicle and industrial IoT deployments | Medium term (2-4 years) |
| Global shortage of HBM3e memory constraining GPU server shipments 2024-26 | -1.1% | Global, with supply bottlenecks concentrated in South Korea and Taiwan | Short term (≤ 2 years) |
| Cyber-sovereignty regulations limiting cross-border HPCaaS workloads | -0.7% | Europe (GDPR), China (Data Security Law), Russia, with spillover to India and Brazil | Long term (≥ 4 years) |
| Source: Mordor Intelligence | |||
Escalating Datacenter Water-Usage Restrictions in Drought-Prone U.S. States
Water scarcity now dictates site selection. California’s 20% industrial-use reduction order forced Tier-3 facilities to retrofit with dry cooling that raises power draw by 15%, adding USD 50 million per site in 2025 retrofit capital.[4]Water Boards Industrial Restrictions, California State Water Resources Control Board, waterboards.ca.gov Arizona halted new groundwater permits in Phoenix, compelling builders to incorporate closed-loop liquid cooling or cancel projects. Google postponed a 200-megawatt Nevada HPC site for lack of water rights, substituting a costlier air-cooled design. Capacity shifts north toward Oregon and Washington, but that realignment increases latency for California-based AI startups that previously enjoyed single-region round-trip times below 10 milliseconds.
Global Shortage of HBM3e Memory Constraining GPU Server Shipments 2024-26
HBM3e stacking yields remain below 60%, capping NVIDIA’s H200 allocations and forcing quota-based deliveries favoring hyperscalers over enterprise buyers. Samsung’s validation delays push meaningful supply into mid-2026, prolonging lead times on Dell’s XE9680 servers, whose backlog ballooned to USD 2 billion in fiscal 2025. Cloud launches slip as well; AWS shifted P5e general availability to mid-2026. A chronic silicon-memory mismatch elevates accelerator pricing and slows rollout of AI inference services, subtracting 1.1% from the compound growth slope of the HPC market.
Segment Analysis
By Component: Services Outpace Hardware as Consumption Models Reshape Procurement
Services recorded the fastest trajectory, expanding at a 9.42% CAGR from 2026 to 2031 as enterprises transition away from multimillion-dollar capital purchases toward pay-per-core-hour contracts. Hardware still accounted for 51.54% of 2025 revenue, but the high performance computing market size for services is projected to surpass USD 30 billion by 2031, closing the historical gap. Managed HPC and HPC-as-a-Service offerings allow aerospace and banking clients to spin up 100,000-core clusters for two-day burst windows instead of locking funds into five-year depreciation cycles, improving budget agility when demand is episodic. System-integration engagements now bundle application porting, code refactoring and performance tuning, particularly for legacy Fortran or C kernels that require GPU-optimized rewrites to exploit concurrency. Within hardware, however, GPU-accelerated nodes remain supply-constrained, and direct-to-chip liquid cooling becomes mandatory as 700-watt devices push rack densities beyond 120 kilowatts.
Professional-services vendors increasingly guarantee performance targets measured in wall-clock hours, not utilization percentages, aligning incentives with customer outcomes. Flash arrays dominate latency-sensitive workloads, while object repositories store exabyte-scale genomics archives. Interconnect sales migrate to 400-gigabit Ethernet for cost-conscious buyers and to InfiniBand NDR for top-end deployments that must train 100-billion-parameter models within 10 days. Software revenue, though smaller, underpins job-scheduling, data-orchestration and hybrid-burst automation, enabling policy-driven placement that factors cloud spot pricing and data-residency rules in the HPC market. Altogether these shifts re-rank vendor margin structures and tilt long-term value capture toward recurring services.

Note: Segment shares of all individual segments available upon report purchase
By Deployment Mode: Hybrid Architectures Reconcile Sovereignty with Elasticity
Cloud held 48.88% of 2025 revenue, but the high performance computing market size for hybrid deployments is projected to expand fastest, growing at 8.22% CAGR through 2031 as security and cost considerations dictate a blended approach. Enterprises discover that sustained workloads exceeding 18 months achieve lower total cost of ownership on owned infrastructure, whereas seasonal or exploratory computations still favor cloud burst. Defense agencies and high-frequency traders, constrained by sub-millisecond latency and air-gapped security mandates, keep control planes on-premise yet outsource parameter sweeps to public clouds during off-hours. Schlumberger’s 2025 migration to a Houston-plus-OCI model underscores the savings potential of hybrid, trimming USD 120 million from projected three-year capital spend.
Operational complexity rises with workload portability, egress fees at USD 0.12 per gigabyte make petabyte shuffling uneconomical, so firms prioritize compute-to-data ratios when selecting execution venues. Kubernetes-native schedulers such as IBM Spectrum LSF and HPE Slingshot automate placement, but compliance officers still vet cross-border data flows to meet GDPR and sector-specific mandates. Cloud providers counter by promising region-locked HPC zones with residency guarantees, but such offerings carry premium pricing. The hybrid surge ultimately reframes the high performance computing market for networking gear, storage gateways and observability stacks tuned for multi-site topologies.
By Chip Type: ASIC and AI Accelerators Challenge GPU Hegemony in Specialized Workloads
GPUs dominated 59.22% of 2025 revenue, yet ASICs and dedicated AI accelerators are forecast to expand at 8.86% CAGR, eroding share as inference eclipses training in aggregate compute hours. Google’s TPU v5e illustrates the trend, delivering 2.5-times A100 throughput for transformer inference while consuming 40% less power. The high performance computing market share advantage of GPUs persists in double-precision tasks like climate modeling, but INT8 and FP8 inference, which constitute most production AI, now favors fixed-function silicon. CPUs remain essential for coordination, I/O and workloads unsuited to massive parallelism; AMD’s 96-core EPYC captures 35% of HPC CPU shipments on core density alone.
Chiplet architectures blur categorical boundaries. NVIDIA’s H200 integrates a transformer engine for FP8 math, while AMD’s MI300 co-locates CPU and GPU tiles using 2.5D packaging to cut memory latency by 40%. FPGAs stay relevant in ultra-low-latency segments such as electronic-options pricing, where microsecond deadlines justify USD 20,000 card prices. CUDA, ROCm, TensorRT, OneAPI and proprietary ASIC toolchains divide developer attention, increasing the fixed cost of adopting additional silicon flavors and complicating procurement decisions for smaller institutions.

Note: Segment shares of all individual segments available upon report purchase
By Industrial Application: Life Sciences Surge Past Traditional Engineering Workloads
Government and defense commanded 24.16% of 2025 revenue owing to nuclear-weapons simulation and intelligence analytics, yet its growth moderates as flagship exascale systems move from construction to utilization. Conversely, life sciences and healthcare exhibit a 9.54% CAGR and are on pace to overtake engineering by 2029, riding the adoption curve of generative-AI-enabled drug discovery. Moderna cut preclinical vaccine screening to 6 months on a 10,000-GPU cluster, tripling annual candidate throughput. The HPC market size for pharmaceutical discovery adds incremental spend on molecular-dynamics engines, quantum chemistry codes and graph neural networks that predict protein–ligand affinity.
Automotive engineering grows at 7.2% CAGR under EU-driven virtual-crash mandates and electrified-vehicle battery simulations that meld electrochemical and thermal solvers. Banking and financial services log 8.1% CAGR as algorithmic traders deploy petaflop-class clusters for overnight Value-at-Risk calculations and fraud-detection models. Energy supermajors stabilize or modestly contract physical datacenters as seismic workload burst to cloud, though high-resolution reservoir models still require on-premise GPUs during exploration drilling windows. The confluence of new biological modeling algorithms and regulatory simulation mandates widens the addressable high performance computing industry pool, reinforcing multi-vertical momentum.
Geography Analysis
North America accounted for 40.48% of 2025 revenue, anchored by USD 3.5 billion in U.S. federal exascale funding and hyperscale cloud operators that annually invest more than USD 200 billion in AI-optimized datacenters. The high performance computing market size in Canada rises as quantum-annealing vendor D-Wave ships 10,000-qubit systems for portfolio optimization, bridging classical–quantum workflows for financial institutions. Mexico’s entrance remains modest, serving nearshored automotive crash simulation through a 5-petaflop General Motors cluster installed in Toluca. Geographically, water-usage curbs in California and datacenter moratoriums in Virginia divert new builds to Oregon, Washington and Texas, subtly re-mapping intra-region latency profiles that historically favored Silicon Valley.
Asia Pacific is projected to grow fastest at 7.98% CAGR, powered by indigenous exascale deployments and sovereign silicon programs. China’s Sunway Oceanlight and follow-on systems circumvent foreign export regimes and enable climate modeling and aerospace design without dependency on Western chips. India’s USD 1.2 billion National Supercomputing Mission 2.0 will install 25 petaflops across academic campuses by 2027, democratizing access for biotech and weather-forecast startups. Japan’s ARM-based Fugaku remains the energy-efficiency benchmark, influencing global CPU roadmaps, while South Korea aligns semiconductor-process simulation clusters with Samsung R&D to accelerate HBM packaging. Singapore’s 15-petaflop expansion positions its national supercomputing center as an ASEAN hub for pharmaceutical and finance workloads. Data residency and cyber-sovereignty laws force multinational enterprises to maintain in-country clusters, giving rise to a fragmented yet fast-growing regional supply chain.
Europe captured 22% of 2025 global revenue. The EuroHPC Joint Undertaking funds exascale-class systems such as Finland’s 309-petaflop LUMI and Italy’s 304-petaflop Leonardo for materials science and climate research. Germany’s JUPITER exascale machine leverages NVIDIA H100 GPUs and eviden BullSequana cabinets to support Volkswagen crash simulations and BASF catalyst design. The EURO-NCAP 2030 mandate remains a structural demand driver for GPU clusters across Germany, France and Italy, while Nordic nations attract private cloud builds thanks to abundant hydroelectric power and free ambient cooling. GDPR-induced residency obligations sustain on-premise and hybrid growth, particularly in healthcare and finance where sensitive records cannot leave national borders.
South America, the Middle East and Africa remain nascent but opportunity-rich. Brazil’s Petrobras operates 10 petaflops for offshore reservoir models, and Saudi Arabia’s KAUST added 15 petaflops in 2024 for renewable-energy and desalination research. The United Arab Emirates commissioned an 8-petaflop cluster for Arabic large-language-model training and smart-city twins. Israel’s Technion expanded to 5 petaflops for cybersecurity analytics, whereas South Africa’s CHPC maintains 4 petaflops for mining and epidemiology. Infrastructure gaps such as intermittent power in Nigeria and severe water scarcity in Gulf states elevate deployment cost, encouraging containerized or modular designs optimized for energy efficiency.

Competitive Landscape
The high performance computing market is moderately concentrated. In hardware, NVIDIA, Intel, AMD, Hewlett Packard Enterprise and Dell Technologies captured about 60% of 2025 revenue; meanwhile, software, cloud services and integration remain fragmented among more than 50 specialized vendors. NVIDIA’s ownership of Mellanox lets it bundle GPUs and InfiniBand switches as a turnkey exascale stack, locking in design wins for El Capitan in the United States and JUPITER in Germany. Hyperscalers counter by vertically integrating: Amazon’s Graviton4 CPU, Google’s TPU v5 and Microsoft’s Maia accelerator sidestep merchant-GPU shortages and reduce marginal cost per inference. Server original-equipment manufacturers navigate shrinking hardware margins by bundling liquid cooling and management services, as Dell’s PowerEdge XE9712 illustrates with rack-unit densities pushing 12 kilowatts.
Start-ups carve out high-value niches. Cerebras’ wafer-scale engine eliminates inter-chip bottlenecks and trains 20-billion-parameter models 10 times faster than eight-GPU nodes in pharma benchmarks. SambaNova exploits reconfigurable dataflow to outperform GPUs on sparse neural networks common in fraud-detection and recommendation workloads. Chiplet approaches gain traction; AMD’s MI300 integrates GPU and CPU dies via 3D stacking, cutting inter-tile latency by 40% and winning Meta and Microsoft deployments in 2025. NVIDIA filed 127 optical-interconnect patents in 2024, suggesting a roadmap toward silicon photonics that could deliver 10 terabit-per-second links, potentially obsoleting copper-based InfiniBand after 2028.
Liquid-cooling retrofits turn into a USD 500 million-plus opportunity by 2026 as states mandate lower water consumption. Vendors such as Asetek and CoolIT now sell direct-to-chip solutions that reduce evaporative losses by 80%, opening expansion paths in drought-affected western United States. These shifts recalibrate value capture along the hardware–services continuum, while cloud-native workflow orchestration reshapes entrant barriers in the broader high performance computing industry.
High Performance Computing Industry Leaders
Advanced Micro Devices, Inc.
NEC Corporation
Hewlett Packard Enterprise
Qualcomm Incorporated
Fujistu Limited
- *Disclaimer: Major Players sorted in no particular order

Recent Industry Developments
- January 2026: NVIDIA began volume shipments of its Blackwell B200 GPU with 208 billion transistors and 20 petaflops of FP4 throughput, supplying Microsoft Azure and Meta’s AI Research SuperCluster.
- December 2025: Hewlett Packard Enterprise secured a USD 1.2 billion U.S. Department of Energy contract to deploy Aurora 2 at Argonne National Laboratory, targeting 2.5 exaflops for nuclear-reactor simulation.
- November 2025: Amazon Web Services launched EC2 P5e instances built on NVIDIA H200 GPUs and 3.2-terabit-per-second Elastic Fabric Adapter networking, enabling 1-trillion-parameter model training.
- October 2025: AMD introduced the Instinct MI325X GPU with 288 gigabytes of HBM3e memory and secured Meta and Oracle Cloud Infrastructure design wins for generative-AI training.
Research Methodology Framework and Report Scope
Market Definitions and Key Coverage
Our study defines the high-performance computing (HPC) market as the annual revenues generated from purpose-built servers, storage subsystems, high-speed interconnects, enabling software, and related professional or managed services that allow organizations to run massively parallel or accelerated workloads in scientific, engineering, analytics, and AI settings.
Scope exclusion: Consumer gaming GPUs sold at retail and generic cloud infrastructure not configured for HPC workloads are excluded.
Segmentation Overview
- By Component
- Hardware
- Servers
- General-Purpose CPU Servers
- GPU-Accelerated Servers
- ARM-Based Servers
- Storage Systems
- HDD Arrays
- Flash-Based Arrays
- Object Storage
- Interconnect and Networking
- InfiniBand
- Ethernet (25/40/100/400 GbE)
- Custom or Optical Interconnects
- Servers
- Software
- System Software (OS, Cluster Management)
- Middleware and RAS Tools
- Parallel File Systems
- Services
- Professional Services
- Managed and HPC-as-a-Service (HPCaaS)
- Hardware
- By Deployment Mode
- On-premise
- Cloud
- Hybrid
- By Chip Type (Cross-Cut with Component)
- CPU
- GPU
- FPGA
- ASIC or AI Accelerators
- By Industrial Application
- Government and Defense
- Academic and Research Institutions
- BFSI
- Manufacturing and Automotive Engineering
- Life Sciences and Healthcare
- Energy, Oil and Gas
- Other Industry Applications
- By Geography
- North America
- United States
- Canada
- Mexico
- Europe
- Germany
- United Kingdom
- France
- Italy
- Nordics (Sweden, Norway, Finland)
- Rest of Europe
- Asia Pacific
- China
- Japan
- India
- South Korea
- Singapore
- Rest of Asia Pacific
- South America
- Brazil
- Argentina
- Rest of South America
- Middle East
- Israel
- United Arab Emirates
- Saudi Arabia
- Turkey
- Rest of Middle East
- Africa
- South Africa
- Nigeria
- Rest of Africa
- North America
Detailed Research Methodology and Data Validation
Primary Research
Our analysts interviewed HPC system integrators, semiconductor architects, cloud-HPC product managers, and directors of national compute centers across North America, Europe, and Asia-Pacific. The conversations tested usage intensity, GPU attach rates, node-hour pricing trends, and procurement lead times, helping us cross-check secondary ratios and refine regional adoption assumptions.
Desk Research
We began by compiling public-domain datasets from tier-one bodies such as the TOP500 list, the US Department of Energy budget justifications, EuroHPC Joint Undertaking grant releases, UN Comtrade HS-8471 trade flows, OECD STAN R&D spend, and academic papers indexed in IEEE Xplore. Company filings, investor decks, and reputable trade portals like HPCwire added vendor shipment context. Select paid repositories, notably D&B Hoovers for financial splits and Dow Jones Factiva for deal flow, supplemented gaps. These sources built the historical baseline, enriched component pricing curves, and flagged policy or funding inflections. The sources named are illustrative; many additional publications informed validation and clarification.
Market-Sizing & Forecasting
A top-down model starts with tracked global shipments of HPC-class servers and storage, augmented by trade reconstruction for gray-channel hardware, which is then multiplied by weighted average selling prices sourced from vendor disclosures and primary checks. Results are sense-checked through selective bottom-up roll-ups of leading suppliers and cloud node consumption logs. Key variables include installed petaflop capacity, government HPC appropriation growth, GPU accelerator penetration, cloud HPC node-hour volumes, and semiconductor ASP movements. Multivariate regression on these indicators, combined with scenario analysis for hyperscale cloud uptake, drives the 2025-2030 forecast. Any sub-segment where bottom-up evidence is thin is prorated using historic component mix trends and validated with expert feedback.
Data Validation & Update Cycle
Outputs pass anomaly scans, year-on-year variance thresholds, and peer review before sign-off. We refresh every twelve months and issue interim revisions when sizable funding awards, export controls, or technology nodes materially alter demand. A final analyst pass is completed immediately prior to report delivery.
Why Mordor's High Performance Computing Baseline Commands Reliability
Published HPC estimates often diverge because providers choose different workload cut-offs, mix hardware with cloud services unevenly, or lock exchange rates at varied points. We acknowledge these realities up front.
Key gap drivers emerge when others fold enterprise AI servers into HPC, apply blanket price erosion without chip-type nuance, or update models infrequently, thereby missing surges in EuroHPC procurements and U.S. CHIPS-funded installations that our rolling dataset already captures.
Benchmark comparison
| Market Size | Anonymized source | Primary gap driver |
|---|---|---|
| USD 55.71 B (2025) | Mordor Intelligence | - |
| USD 61.68 B (2025) | Global Consultancy A | Counts enterprise AI hardware inside scope, inflating base value |
| USD 54.39 B (2024) | Analytics Firm B | Separates HPCaaS revenues, leading to partial double counting |
| USD 49.90 B (2027) | Research Publisher C | Omits software and managed services; uses older server price bands |
The comparison shows that once scope alignment and recent funding waves are normalized, Mordor's figure sits mid-range, giving decision-makers a balanced reference grounded in transparent variables and a refresh cadence that stays in step with the rapidly evolving HPC landscape.
Key Questions Answered in the Report
What is the projected value of the high performance computing market in 2031?
The market is forecast to reach USD 87.50 billion by 2031.
Which segment is expected to grow fastest within the high performance computing market?
Services, driven by managed HPC and HPC-as-a-Service offerings, is projected to grow at a 9.42% CAGR through 2031.
Why are hybrid deployments gaining ground?
Hybrid architectures balance data-sovereignty and security needs with the elasticity of cloud resources, delivering an 8.22% CAGR growth advantage.
How will HBM3e supply constraints affect future system purchases?
Limited HBM3e yields prolong GPU server lead times into 2027, raising acquisition costs and encouraging buyers to consider ASIC and CPU alternatives.
Which region is expanding fastest in high performance computing adoption?
Asia Pacific is forecast to record a 7.98% CAGR between 2026 and 2031, fueled by indigenous exascale projects and pharmaceutical outsourcing demand.
What cooling technology trend addresses water-usage regulations in the United States?
Direct-to-chip liquid-cooling retrofits reduce evaporative consumption by up to 80%, facilitating datacenter expansion in drought-prone states.




