#High-Performance Computing HPC as a Service Market Research

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AWS 2025: New Features and Changes You Should Know

Discover the key AWS 2025 updates, including new AI tools, instance types, cost-saving features, and security enhancements, plus how startups and enterprises can leverage them for smarter scaling and cloud optimization.

AWS continues to lead the cloud market by rolling out a torrent of new services and enhancements. In this blog, we cover the AWS 2025 updates and AWS new features 2025 that startups and enterprises should watch. You will learn what’s new in AWS 2025, from generative AI to new instance types, and see how the AWS roadmap 2025 is shaping trends in scalability, security, and cost. 

We also highlight AWS for startups USA, cost optimization strategies, and AWS security features 2025. Finally, we share a real-world example – a Logiciel case study on optimizing AWS for JobProgress (Leap LLC) – to demonstrate dramatic AWS cost optimization 2025 results and performance gains.

Generative AI and Machine Learning Innovations

AWS is investing heavily in AI/ML, reflecting the trend of AI-powered cloud services. Key highlights include:

Bedrock Data Automation (GA) – Now generally available, this feature automates generation of insights from multimodal content (documents, images, video, audio), helping developers build generative AI applications faster. Bedrock includes over 100 new foundation models, giving startups and enterprises more flexibility and control in deploying AI models.

SageMaker AI Enhancements – SageMaker has new capabilities for large-model training and more third-party model integrations, which streamline AI development while reducing cost and effort. SageMaker is widely adopted to build, train, and deploy models, and these improvements help accelerate AI adoption and cost efficiency.

Conversational AI Tools – AWS’s new tools like Q Developer and Q Business are getting smarter. Q Developer now has an enhanced CLI agent for dynamic code and conversation interaction and can generate documentation, code reviews, and tests in IDEs. Meanwhile, Q Business adds 50+ workflow integrations for automating enterprise tasks.

Hardware for AI – AWS launched faster AI chips. EC2 Trn2 instances (Trainium2-based) deliver faster speed, more memory bandwidth, and higher compute performance for ML training and inference. Also, EC2 P5en instances with high-bandwidth GPUs offer massive networking throughput for deep learning and HPC workloads.

AWS’s 2025 priority on AI is clear from its strategy. The company is even funding AI with a multi-million dollar accelerator program and public-sector research support. For startups, AWS offers cloud credits to experiment with these new AI services. Taken together, the AWS innovations 2025 for startups are vast: from Bedrock and SageMaker enhancements to Q AI assistants, AWS is making generative AI a first-class citizen in the cloud.

Compute, Storage, and Networking Enhancements

AWS continues to expand its core infrastructure with new instance types, chips, and network features:

New EC2 Instances – Several new instance families launched recently

I8g Instances – Storage-optimized instances with next-gen processors and SSDs boost I/O-intensive workloads.

I7ie Instances – Storage-optimized with massive NVMe support and better compute performance.

P5en Instances – Designed for AI/HPC, with ultra-high-speed networking.

Trn2 (Trainium2) Instances – Boosts ML model training with faster compute and memory.

Networking and Zones – AWS is boosting networking and local expansion with advanced adapters and improved VPC tools for securely orchestrating hybrid workflows. Local Zones and Outposts continue expanding in U.S. cities for low-latency edge computing.

Global Infrastructure – AWS is scaling its footprint with new designs for power-efficient data centers. While no new U.S. regions were launched yet, expect continued growth in availability zones and networking capabilities.

Containers, Serverless, and Cloud Services

AWS is also improving its container and serverless offerings, which many startups and microservices architectures rely on:

Kubernetes and Container Management – Enhanced features now auto-encrypt Kubernetes API data and offer Auto Mode for provisioning compute, storage, and networking. EKS Hybrid Nodes let you run Kubernetes on-prem alongside the cloud. These reduce operational overhead and improve governance.

Serverless (Lambda, Fargate, etc.) – Continued refinements in performance and flexibility help developers run code without managing servers. Improvements include faster cold starts and more memory/CPU configurations.

Application Services – Data pipelines are getting streamlined with zero-ETL connections. Event-driven services and secure hybrid integration features have been added. Messaging services now support generative AI capabilities for enhanced customer interactions.

These AWS cloud services 2025 focus on reducing the management burden. Kubernetes is more secure and easier; serverless offerings get performance boosts; and data workflows become more automated. For startups and enterprises alike, this means faster deployments and consistent governance.

Security and Compliance Enhancements

Security is a top focus for AWS in 2025:

Encryption and Protection by Default – Key services now encrypt data automatically. Malware protection is enabled by default. New incident response tools guide organizations through remediation using predefined playbooks.

Secure AI Use – AWS is prioritizing safe AI development. Features include content filters and policy-driven AI guardrails to manage generative outputs responsibly.

Compliance and Identity – AWS continues expanding its certifications and offers stronger access controls and audit features to simplify compliance for U.S.-based organizations.

Cost Optimization and Pricing Changes

Cost control is always critical, especially for startups on tight budgets. AWS 2025 brings both new tools and policy changes:

Reserved Instance / Savings Plan Policy – Effective June 1, 2025, AWS is restricting RIs and Savings Plans to a single end customer’s usage. In practice, this means MSPs and resellers can no longer share one RI/SP across multiple clients. Enterprises should review their commitments: the new policy could require each company (or corporate unit) to manage its own reservations separately​. This is a major AWS pricing change 2025 and may impact how large organizations do bulk purchasing.

Spot Instances and Fargate Spot – AWS continues to encourage spot pricing: new visibility tools and deeper discounts (up to 90%) help automate migrating workloads to spot when possible. For example, AWS Batch and SageMaker now integrate Spot more seamlessly.

Cost Management Tools – AWS enhanced Cost Explorer and Budgets in late 2024, adding features like cost anomaly detection powered by ML. Compute Optimizer was updated to support more resource types and provide savings recommendations (rightsizing instances, using Savings Plans, etc.). Startups should leverage these to track their spending.

Case Study: Leap (JobProgress) – Scalable, Cost-Optimized AWS Architecture

To ground these concepts, consider a real success story. Logiciel worked with JobProgress (Leap LLC), a SaaS CRM for contractors, to redesign their AWS architecture for scale and cost efficiency. Here are the highlights:

Scalable AWS Architecture: By adopting microservices on EKS (Kubernetes) and serverless components, Logiciel made the system cloud-native. This change enabled JobProgress to scale from a few users to 15,000+ active users without performance bottlenecks, learn more here logiciel.io. Auto-scaling and container orchestration ensured reliability during traffic spikes.

Cost Reduction: Through an AWS Well-Architected review, Logiciel identified idle resources and oversized instances. They shifted workloads to spot instances and right-sized instances (using AWS Compute Optimizer recommendations). Combined with Savings Plans, these moves cut AWS infrastructure costs by roughly 40%. The savings came without sacrificing uptime – in fact, database queries became faster by using Aurora Serverless and MemoryDB.

Performance Improvement: Logiciel optimized the database layer (introducing Amazon DynamoDB and Aurora) and caching (Redis via MemoryDB), drastically reducing API latency. Network and security were tightened using VPC endpoints and default encryption. The result was snappier performance: page loads and API calls sped up by an estimated 30%, improving user experience.

Outcome: Within five years of launch, JobProgress’s enhanced AWS platform attracted investors and led to an acquisition by Leap (at a multi-million-dollar valuation). (See the full JobProgress (Leap LLC) case study on Logiciel’s site for a deep dive.) This story shows how AWS cost optimization 2025 techniques can directly power business growth: optimized infrastructure enabled rapid scaling while preserving budget.

Looking Ahead: AWS Roadmap 2025 and Future Trends

What’s on the horizon for AWS beyond these immediate changes? While AWS rarely publishes a roadmap, we can anticipate the direction:

More AI Everywhere: Expect deeper AI integration in all services (e.g. AI-driven DevOps, security, analytics). Amazon Q will likely expand to other AWS consoles and new domains (we’ve already seen Q for coding, BI, workflow).

Evolved Compute Hardware: After Graviton4 and Trainium2, keep an eye on GPU/EFA advances and the next Graviton generation. There may also be new specialized chips (e.g. Inferentia3 for edge AI).

Extended Hybrid and Edge: AWS will grow Local Zones in more U.S. metros, plus expand Wavelength for 5G. Outposts and Local Zones might gain additional service support (e.g. RDS on Local Zones). This fits the U.S. emphasis on data sovereignty and low-latency sectors (finance, manufacturing, media).

Serverless and Managed Services: AWS will continue converting more services to serverless or managed models (e.g. RDS Serverless v2 is rolling out, and Fargate improvements are ongoing). Automation features (like AWS Backup support across more services) will simplify operations.

Billing and FinOps Tools: We may see enhancements to cost management – for example, more granular Spot pricing tools or AI-driven spend forecasts. The recent RI/SP policy change hints AWS wants customers to manage commitments more directly; next might come more flexible consumption models.

Conclusion

AWS’s momentum in 2025 is unmistakable. From AI breakthroughs to new instance families and tighter security defaults, the AWS changes 2025 mean faster innovation for businesses. Startups (leveraging AWS Activate) and enterprises (using AWS Partner programs) will both find powerful new tools to cut costs and speed development. By staying current with AWS 2025 updates whether through official news or consultancies like Logiciel organizations can fully exploit the cloud’s promise.

For a concrete example, check out Logiciel’s success stories including the Leap (JobProgress) case study. It’s proof that applying these AWS innovations leads to real-world gains: cost reduction, performance improvement, and business growth. As AWS security features 2025 and new cloud services roll out, the clear strategy is to embrace them proactively. With careful planning and expert guidance, AWS users can harness these changes and stay competitive in the dynamic tech landscape.

[cybersecurityict]

High-Performance Computing Market Size, Share, Analysis, Forecast, and Growth Trends to 2032: Powering Advanced Scientific Research

High-Performance Computing Market was worth USD 47.07 billion in 2023 and is predicted to be worth USD 92.33 billion by 2032, growing at a CAGR of 7.80 % between 2024 and 2032.

High-Performance Computing Market is undergoing a dynamic transformation as industries across the globe embrace data-intensive workloads. From scientific research to financial modeling, the demand for faster computation, real-time analytics, and simulation is fueling the rapid adoption of high-performance computing (HPC) systems. Enterprises are increasingly leveraging HPC to gain a competitive edge, improve decision-making, and drive innovation.

High-Performance Computing Market is also seeing a notable rise in demand due to emerging technologies such as AI, machine learning, and big data. As these technologies become more integral to business operations, the infrastructure supporting them must evolve. HPC delivers the scalability and speed necessary to process large datasets and execute complex algorithms efficiently.

Get Sample Copy of This Report: https://www.snsinsider.com/sample-request/2619 

Market Keyplayers:

NEC Corporation

Hewlett Packard Enterprise

Sugon Information Industry Co. Ltd

Intel Corporation

International Business Machines Corporation

Market Analysis

The HPC market is characterized by strong investment from both government and private sectors aiming to enhance computational capabilities. Healthcare, defense, automotive, and academic research are key segments contributing to the rising adoption of HPC. The proliferation of cloud-based HPC and integration with AI are redefining how organizations manage and process data.

Market Trends

Increasing integration of AI and ML with HPC systems

Growing popularity of cloud-based HPC services

Shift towards energy-efficient supercomputing solutions

Rise in demand from genomics, climate modeling, and drug discovery

Accelerated development in quantum computing supporting HPC evolution

Market Scope

The potential for HPC market expansion is extensive and continues to broaden across industries:

Healthcare innovations powered by HPC-driven diagnostics and genomics

Smart manufacturing leveraging real-time data analysis and simulation

Financial analytics enhanced by rapid processing and modeling

Scientific research accelerated through advanced simulation tools

Government initiatives supporting HPC infrastructure development

These evolving sectors are not only demanding more robust computing power but also fostering an ecosystem that thrives on speed, accuracy, and performance, reinforcing HPC's pivotal role in digital transformation.

Market Forecast

The future of the HPC market holds promising advancements shaped by continuous innovation, strategic partnerships, and increased accessibility. As industries push for faster processing and deeper insights, HPC will be central in meeting these demands. The convergence of HPC with emerging technologies such as edge computing and 5G will unlock new possibilities, transforming how industries analyze data, forecast outcomes, and deploy intelligent systems. The market is poised for exponential growth, with cloud solutions, scalable architectures, and hybrid models becoming the norm.

Access Complete Report: https://www.snsinsider.com/reports/high-performance-computing-market-2619 

Conclusion

The High-Performance Computing Market is more than a technological trend—it is the backbone of a data-driven future. As industries demand faster insights and smarter decisions, HPC stands as a transformative force bridging innovation with execution. Stakeholders ready to invest in HPC are not just adopting new tools; they are stepping into a future where speed, intelligence, and precision define success.

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[industrynewsupdates]

Future of GPU As A Service Market: Trends and Forecast

The global GPU as a Service (GPUaaS) market is projected to reach USD 12.26 billion by 2030, growing at a CAGR of 22.9% from 2025 to 2030, according to a recent report by Grand View Research, Inc. This growth is being largely fueled by the increasing deployment of Artificial Intelligence (AI) and Machine Learning (ML) technologies across a wide range of industries. These technologies require extensive computational resources, a demand that Graphics Processing Units (GPUs) are well-equipped to meet. GPUaaS offers users the advantage of scalability, enabling them to adjust computing power in alignment with project-specific needs. As a result, demand for GPUaaS is rising in tandem with the broader adoption of AI and ML.

The rapid expansion of cloud computing has further accelerated the growth of GPUaaS. Leading cloud service providers are offering GPU-powered virtual machines to support tasks such as deep learning, data processing, graphics rendering, and scientific computing. These services democratize access to powerful computing capabilities, making high-performance GPUs available to users who may not be able to afford or manage on-premise hardware. For example, Amazon Web Services (AWS) delivers a range of GPU instances through its Amazon EC2 platform, designed to support varying computational requirements.

GPUaaS gives users—whether enterprises or individual developers—the flexibility to scale their GPU usage dynamically, adapting to different workload demands. This elasticity is especially attractive for organizations with fluctuating or project-based GPU needs. Google Cloud Platform (GCP) exemplifies this flexibility by offering high-performance GPU instances such as NVIDIA A100 Tensor Core GPUs, which are built on the NVIDIA Ampere architecture. These GPUs provide significant performance gains, particularly for AI, ML, and high-performance computing (HPC) workloads.

North America leads the market in terms of revenue generation. The region’s strong emphasis on digital transformation, particularly among enterprise sectors, makes GPUaaS a strategic asset in deploying AI and big data technologies. North America plays a critical role in the global cloud ecosystem, with increasing investments in infrastructure to support GPU-intensive operations.

On the other hand, the Asia Pacific region is anticipated to be the fastest-growing market over the forecast period. This growth is attributed to the region’s proactive adoption of emerging technologies, with countries like China, India, Japan, South Korea, Australia, and Singapore leading the way. Their investments in AI research, smart cities, and digital platforms continue to fuel the demand for scalable GPU resources.

Curious about the GPU As A Service Market? Download your FREE sample copy now and get a sneak peek into the latest insights and trends. 

GPU as a Service (GPUaaS) Market: Frequently Asked Questions

1. What is the expected size of the GPUaaS market by 2030?

The global GPUaaS market is projected to reach USD 12.26 billion by 2030, growing at a CAGR of 22.9% from 2025 to 2030.

2. What’s driving the demand for GPUaaS?

Rising adoption of AI and ML, increasing data volumes, demand for flexible cloud computing solutions, and growing use of GPU-accelerated applications across industries.

3. What are the benefits of GPUaaS?

• Scalability on demand

• Cost-efficiency

• Easy integration with AI and data analytics tools

• Faster time-to-market for compute-heavy applications

4. Which industries benefit most from GPUaaS?

Key sectors include:

• Healthcare (medical imaging, genomics)

• Finance (fraud detection, algorithmic trading)

• Automotive (autonomous vehicle training)

• Entertainment (3D rendering, VFX)

• Research & academia

5. Which region leads the GPUaaS market?

North America is the largest market, driven by strong cloud infrastructure, tech adoption, and enterprise digital transformation efforts

6. Which region is expected to grow the fastest?

Asia Pacific is anticipated to grow rapidly due to aggressive investment in emerging tech by countries like China, India, Japan, and South Korea.

Order a free sample PDF of the GPU As A Service Market Intelligence Study, published by Grand View Research.

[gis56]

🔬 Bioinformatics Platforms: Big Data’s Role in Precision Medicine & Genomics 📊🧪

Advanced Bioinformatics Platforms Market is revolutionizing genomics, proteomics, and metabolomics research, enabling breakthroughs in personalized medicine, drug discovery, and biotechnology. With AI-driven analytics, cloud-based solutions, and high-performance computing, bioinformatics platforms are shaping the future of life sciences and healthcare.

To Request Sample Report: https://www.globalinsightservices.com/request-sample/?id=GIS32733 &utm_source=SnehaPatil&utm_medium=Article

🔬 Key Market Trends & Innovations

✅ Genomics & Proteomics Driving Growth: Unlocking precision medicine & targeted therapies. ✅ AI & Machine Learning Integration: Enhancing data mining, predictive modeling & diagnostics. ✅ Cloud-Based & Hybrid Solutions Rising: Enabling scalable, secure & real-time data analysis. ✅ Blockchain in Bioinformatics: Ensuring data integrity, security & collaboration. ✅ High-Performance Computing (HPC) Expansion: Processing massive biological datasets efficiently.

📊 Market Segmentation & Growth

🔹 Technology: AI, Cloud Computing, HPC, Blockchain, Data Visualization 🔹 Products: Software Platforms, Databases, Analytical Tools, Workflows 🔹 Services: Data Analysis, Consulting, Custom Development, Training & Support 🔹 Applications: Drug Discovery, Clinical Diagnostics, Forensic Science, Personalized Medicine 🔹 End Users: Biotech & Pharma Companies, Research Institutes, Healthcare Providers

🌍 Regional Market Insights

🇺🇸 North America dominates with cutting-edge genomic research & AI-powered bioinformatics. 🇩🇪 Europe follows closely, backed by government support for personalized medicine & biotech innovation. 🇨🇳 Asia-Pacific sees rapid growth, with China & India investing in bioinformatics & precision healthcare. 🇧🇷 Latin America adopts bioinformatics, with Brazil leading healthcare & biotech advancements. 🇦🇪 Middle East & Africa integrate bioinformatics, focusing on healthcare digitization & genomic medicine.

📈 Future Outlook

📊 With AI, HPC & blockchain transforming bioinformatics, the market is set for exponential growth! 🏆 Top Players: Illumina, Thermo Fisher Scientific, Qiagen, Agilent Technologies, IBM Watson Health, PerkinElmer.

The future of bioinformatics, genomics, and precision healthcare is here, powered by advanced computational platforms! 🧬🚀

#bioinformatics #genomics #precisionmedicine #drugdiscovery #artificialintelligence #machinelearning #proteomics #pharmacogenomics #healthcareinnovation #cloudcomputing #genomeanalysis #genetherapy #aiinhealthcare #hpc #computationalbiology #personalizedmedicine #nextgensequencing #clinicaldiagnostics #bigdata #biotechresearch #medicalai #datadrivenhealthcare #moleculardiagnostics #agriculturalbiotech #genomeediting #biotechstartups #forensicscience #lifesciences #genomeinformatics #blockchaininhealthcare

[boom3010]

In-Memory Computing Chips: The Next Big Thing? Market to Hit $12.4B by 2034

In-Memory Computing Chips Market is experiencing rapid growth as industries demand faster data processing, real-time analytics, and energy-efficient computing. Unlike traditional architectures, in-memory computing chips store and process data in the same location, eliminating latency and dramatically improving performance. This breakthrough technology is transforming industries such as AI, big data, edge computing, healthcare, finance, and autonomous systems.

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Why In-Memory Computing Chips?

✅ Accelerate AI & machine learning applications ✅ Enable real-time big data analytics ✅ Reduce power consumption & latency ✅ Optimize cloud computing & edge AI

Market Growth Drivers:

📈 Growing demand for AI-driven computing & deep learning 📈 Expansion of IoT, 5G, and high-performance computing (HPC) 📈 Rising need for energy-efficient data centers & cloud infrastructure 📈 Advancements in neuromorphic and resistive RAM (ReRAM) technologies

The global in-memory computing chips market is set to expand, with major tech giants and startups investing in AI accelerators, neuromorphic computing, and next-gen memory architectures. As AI, blockchain, and real-time analytics continue to evolve, in-memory computing is emerging as a critical enabler of high-speed, low-latency processing.

With quantum computing and edge AI pushing the limits of traditional computing, in-memory computing chips are paving the way for a faster, smarter, and more efficient digital future.

What are your thoughts on in-memory computing? Let’s discuss! 👇

#InMemoryComputing #AIAccelerators #EdgeAI #HighPerformanceComputing #BigData #RealTimeAnalytics #CloudComputing #MachineLearning #ArtificialIntelligence #NeuromorphicComputing #NextGenChips #TechInnovation #AIChips #DataProcessing #DeepLearning #IoT #5G #QuantumComputing #SmartComputing #ChipTechnology #EnergyEfficientTech #HPC #DataCenters #ReRAM #CloudAI #AIHardware #FutureOfComputing #FastProcessing #LowLatency #NextGenMemory 🚀

Research Scope:

· Estimates and forecast the overall market size for the total market, across type, application, and region

· Detailed information and key takeaways on qualitative and quantitative trends, dynamics, business framework, competitive landscape, and company profiling

· Identify factors influencing market growth and challenges, opportunities, drivers, and restraints

· Identify factors that could limit company participation in identified international markets to help properly calibrate market share expectations and growth rates

· Trace and evaluate key development strategies like acquisitions, product launches, mergers, collaborations, business expansions, agreements, partnerships, and R&D activities

About Us:

Global Insight Services (GIS) is a leading multi-industry market research firm headquartered in Delaware, US. We are committed to providing our clients with highest quality data, analysis, and tools to meet all their market research needs. With GIS, you can be assured of the quality of the deliverables, robust & transparent research methodology, and superior service.

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[blueweave8]

Immersion Cooling Market Analysis, Demand, Report 2023-2030

BlueWeave Consulting, a leading strategic consulting and market research firm, in its recent study, estimated Global Immersion Cooling Market size at USD 780 million in 2023.During the forecast period between 2024 and 2030, BlueWeave expects Global Immersion Cooling Market size to boom at a robust CAGR of 24.20% reaching a value of USD 3,311.60 million by 2030. Global Immersion Cooling Market is driven by a growing demand for energy-efficient cooling solutions in data centers to reduce power consumption and carbon footprints. Increasing adoption of high-performance computing (HPC), AI, and blockchain technologies generates immense heat, necessitating advanced cooling methods. Rising data center construction, particularly in regions with harsh climates, further boosts demand. Additionally, immersion cooling offers benefits like reduced operational costs, improved server lifespan, and enhanced performance, driving its adoption across industries globally.

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Opportunity - Increasing Adoption in High-Performance Computing (HPC)

Global Immersion Cooling Market is expected to be driven by its increasing adoption in High-Performance Computing (HPC) applications. HPC systems require efficient cooling solutions to handle extreme heat generated by advanced processors and GPUs. Immersion cooling offers superior thermal management, reducing energy consumption and improving system performance. Industries like data centers, artificial intelligence, and scientific research are accelerating the adoption of HPC, boosting demand for immersion cooling solutions. The shift enhances operational efficiency and sustainability. It, in turn, is expected to boost the growth of Global Immersion Cooling Market in the coming years.

Impact of Escalating Geopolitical Tensions on Global Immersion Cooling Market  

Escalating geopolitical tensions could disrupt Global Immersion Cooling Market by impacting supply chains, particularly for critical components like heat exchangers, coolants, and semiconductors. Trade restrictions, sanctions, and rising energy costs may hinder production and increase prices. Additionally, regional instabilities could delay investments in infrastructure developments and data center expansions. However, heightened energy security concerns could drive the adoption of energy-efficient technologies like immersion cooling, particularly in regions aiming to reduce dependence on unstable energy supplies and achieve sustainable operations.

High-Performance Computing (HPC) Segment Leads Global Immersion Cooling Market  

The high-performance computing (HPC) segment holds the largest share of Global Immersion Cooling Market. Immersion cooling is extensively adopted in HPC applications because of its superior capability to handle the significant heat output produced by advanced computing systems. These systems, which are commonly found in data centers and research facilities, leverage immersion cooling to enhance performance, minimize energy usage, and lower cooling expenses. The segment's growth is primarily fueled by the rising need for faster and more powerful computational systems.

Competitive Landscape

Global Immersion Cooling Market is fiercely competitive, with numerous companies vying for a larger market share. Major companies in the market include Green Revolution Cooling (GRC), Submer, LiquidStack, Asperitas, Midas Immersion Cooling, Iceotope Technologies, LiquidCool Solutions, DUG Technology, DCX - The Liquid Cooling Company, Engineered Fluids, TIEMMERS, and TMGcore. These companies use various strategies, including increasing investments in their R&D activities, mergers, and acquisitions, joint ventures, collaborations, licensing agreements, and new product and service releases to further strengthen their position in Global Immersion Cooling Market.

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BlueWeave Consulting & Research Pvt Ltd

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[global-research-report]

Data Center Accelerator Market Analysis: Meeting the Demand for Real-Time Data Processing

The global data center accelerator market size is anticipated to reach USD 63.22 billion by 2030, according to a new report by Grand View Research, Inc. The market is expected to grow at a CAGR of 24.7% from 2025 to 2030. The demand for data center accelerators is likely to grow owing to increasing adoption of technologies such as AI, IoT, & big data analytics. The COVID-19 pandemic had a positive impact on the data center accelerator market. Factors such as increased corporate awareness of the advantages that cloud services can offer, increased board pressure to provide more secure & robust IT environments, as well as the establishment of local data centers contributed to the growth of data center accelerators. Demand for businesses that rely on digital infrastructure has increased, which has led to significant growth in demand for data center network services in many industries. Data centers are now maintaining program availability and data security as more businesses and educational institutions already moved online.

Top industries using HPC are healthcare, manufacturing aerospace, urban planning, and finance. The University of Texas at Austin researchers are advancing the science of cancer treatment through the use of HPC. In a ground-breaking 2017 project, researchers examined petabytes of data to look for connections between the genomes of cancer patients and the characteristics of their tumors. This paved the way for the university to apply HPC in additional cancer research, which has now expanded to include efforts to diagnose and treat cases of prostate, blood-related, liver, and skin cancers.

Data Center Accelerator Market Report Highlights

Based on processor, the GPU segment accounted for the maximum revenue share of 44% in 2024. This can be attributed to the increasing use of GPU acceleration in IoT computing, bitcoin mining, AI and machine learning, etc. Moreover, GPU acceleration’s parallel processing architecture is useful in life science analytics such as a genome sequencing.

Based on type, the HPC data center segment is expected to grow at the highest CAGR of 26.0% over the forecast period. This can be attributed to a rising preference for hybrid and cloud-based high performance computing (HPC) solutions, use of HPC in vaccine development, advances in virtualization, etc.

Based on application, the deep learning training segment dominated the market in 2024. This can be attributed to increasing adoption of deep learning in hybrid model integration, self-supervised learning, high performance natural language process (NLP) models, and neuroscience based deep learning.

North America held the largest share of 37.0% in 2024 and is expected to retain its position over the forecast period. Presence of several data center accelerator solution and service providers makes North America a promising region for the market.

Asia Pacific is anticipated to expand at the highest CAGR of over 27.8% over the forecast period. Suitable government policies and the need for data center infrastructure upgradation in Asia Pacific are driving the growth of the data center accelerator market in the region.

In October 2020 Intel Corporation launched Intel Xeon Scalable Platform to assist secure sensitive workloads. This platform has new features that include Intel Platform Firmware Resilience (Intel PFR), Intel Total Memory Encryption (Intel TME), and new cryptographic accelerators to support the platform and advance the overall integrity and confidentiality of data.

Data Center Accelerator Market Segmentation

Grand View Research has segmented the global data center accelerator market report based on processor, type, application, and region:

Data Center Accelerator Processor Outlook (Revenue, USD Billion, 2018 - 2030)

GPU

CPU

FPGA

ASIC

Data Center Accelerator Type Outlook (Revenue, USD Billion, 2018 - 2030)

HPC Data Center

Cloud Data Center

Data Center Accelerator Application Outlook (Revenue, USD Billion, 2018 - 2030)

Deep Learning Training

Public Cloud Interface

Enterprise Interface

Data Center Accelerator Regional Outlook (Revenue, USD Billion, 2018 - 2030)

North America

US

Canada

Mexico

Europe

UK

Germany

France

Asia Pacific

China

India

Japan

Australia

South Korea

Latin America

Brazil

Middle East & Africa (MEA)

UAE

Saudi Arabia

South Africa

List of Key Players

Advanced Micro Devices, Inc.

Dell Inc.

IBM Corporation

Intel Corporation

Lattice Semiconductor

Lenovo Ltd.

Marvell Technology Inc.

Microchip Technology Inc.

Micron Technology, Inc.

NEC Corporation

NVIDIA Corporation

Qualcomm Incorporated

Synopsys Inc.

Order a free sample PDF of the Data Center Accelerator Market Intelligence Study, published by Grand View Research.

[trescong]

New Age Technologies Paving the Way for Advanced Healthcare

The global health care services have witnessed rapid digitalization leading to better patient outcomes and improvement in the health of the patients. Technology has played a huge role here, with respect to how health care was provided and received across the globe. New age tech, especially Artificial Intelligence (AI) is at the forefront of this revolution. There are a number of use cases where implementation of AI in healthcare has resulted in multiple benefits in areas such as drug discovery, personalized care for chronic diseases, predictive healthcare diagnosis, etc. and at the same time playing a vital role in helping the world fight the pandemic. 

With the help of AI and machine learning, healthcare industry around the globe was able to derive better insights and provide personalized care facility to the patients. There is no doubt that decision makers in the sector understood the importance of technology adoption and areadopting these emerging technologies to reach new heights. 

Healthcare industry has been doing trail run, pilot- projects with several technology development, but adoption of AI and High-performance computing (HPC), has benefitted the most. The democratization of AI and HPC, organizations of any size and from any industry can now gain a competitive edge by harnessing the power of data. The modular building block approach of deployment-ready solutions bring speed and flexibility by allowing for quick set-up and easy scaling. While technology over the years is playing a central role to advancements in medical research, pharmaceutical development and treatments, HPC is helping to boost the sector. With the adoption of IoT sensors, and 5G technology in coming times, we're going to witness data explosion and analysis that will transform the healthcare industry, resulting in more personalized and better medications for all. Thanks to the convergence of HPC, data analytics and AI, the healthcare sector is set to become data-driven and better equipped to respond in more personalized ways. 

Big data leading to big advancements in healthcare 

Life sciences and medical research institutions, particularly genomics and precision medicine are applying AI in remarkable ways, thanks to innovative machine learning models, trained using data from old experiments. By analyzing the genetic designs, researchers can approach each case with more efficiency and accuracy. They can customize treatment models to prescribe the most effective drugs, while at the same time avoiding side effects. 

Accelerated genomic sequencing have a marvelous impact on the global fight against COVID-19, since the insights derived through this technique means faster understanding of the sub strains of the virus, its infectiousness, and a modelling on how it spreads through a population. 

Using data to drive personalized healthcare 

Personalized use of smart devices mean more data to drive health insights. In the next few year, we will witness smart households driving health outcomes through better monitoring at the edge and fast medical responses. Since we are already well accustomed to wearing devices to track our exercise and fitness levels, interpreting that data with AI and HPC will aid in early diagnosis of health problems and help to set the appropriate pathway for treatment. Imagine a time when an individual can accurately understand their health condition before even speaking to a doctor. 

Technology that advances humanity 

As access to AI and HPC becomes part of medical research every day, we can expect to see more organizations reaping the rewards by integrating AI into their infrastructure. We can anticipate that the market will continue to expand with HPC, AI and data analytics solutions and tooling converge. Additionally, we will see the adoption of Graphics Processing Units (GPUs) continue to drive AI, which will pave the way for a new line of Intelligent Processing Units (IPUs). Combined, this will further accelerate the role of data across all industries and while adopting new ways of working can seem daunting for organizations, technology vendors are well-positioned to help businesses navigate unfamiliar terrain. 

Medical research has already achieved massive success with both AI and HPC. By automating baseline data interrogation, humans are free to focus on the finer points of research and discovery. For the areas of healthcare and medical research, HPC will be the critical and X factor in the fight against the diagnosis of rare diseases, paving the way for a new era of preventative healthcare. 

About the Author: 

Manish Gupta, Senior Director & General Manager, Infrastructure Solutions Group, Dell Technologies India. 

[darshanhiranandani-blog]

Darshan Hiranandani on Revolutionizing GPU Computing: Yotta Data Services Partners with NVIDIA

NVIDIA, a leading GPU maker, partners with Darshan Hiranandani’s Yotta Data Services., which is India’s foremost service provider of the data centre and cloud, to transform its journey and embrace the power of GPU computing. This partnership establishes a new ginormous benchmark in GPU computing with the resulting shift of the data-driven creation models through enhancing the rates of digital transformation in numerous industries.

Through collaboration with NVIDIA, Yotta Data Services expects to usher in a new era of versatile computational power and efficiency, backed by NVIDI's state-of-the-art GPU technology which is aimed to give the company's clients unprecedented performance and scalability. Thanks to an in-house developed purpose of the company, Yotta Data Services is all set to bring a major revolution in AI, machine learning, data analytics and scientific research, not in India only but the world as well.

The cooperation between Yotta Data Services and NVIDIA embraces a myriad of efforts both about spreading the power of GPU and boosting creation. Since its announcement, Yotta Data Services has been investing heavily in NVIDIA H100 Tensor Core GPUs, with a plan to have a thousand of these GPUs running in their data centres by 2024. By strategic placement of AI infrastructure, our Yotta Data Services will be capable of providing high-performance computing (HPC) and artificial intelligence (AI) on a massive scale, allowing various businesses, startups, and research institutions to realize new opportunities that exist in the sphere of AI-driven decision-making. It is one of the crucial components of the alliance that NVIDIA is providing its customers with NVIDIA InfiniBand networking along with the NVIDIA-powered reference architectures which is offering opportunities to the firm for the deployment of technology for large-scale AI training, inferencing, and HPC applications. Moreover, Darshan Hiranandani’s Yotta Data Services will release to the market a full range of PaaS solutions, including AI Center Models and applications, to create conditions for quicker development of AI-centric solutions.

With the impressive speed of India's digital economy, a partnership between Darshan Hiranandani’s Yotta Data Services and NVIDIA is likely to generate new technologies and increase a young economy initiative. Yotta Data Services is now aiming to reinvent GPU computation by setting the groundwork for a day-to-day limitless futuristic relay to computation power. Organizations worldwide will be able to unmask the full power of data-driven innovation.

As India witnesses this digital transformation progress, the alliance between Yotta Data Services and NVIDIA seem to be an excellent opportunity for financial institutions including banking, manufacturing, healthcare and so on. Yotta Data Services is welcoming the advancement in technology by democratizing access to GPU computing and conceptualizing AI Infrastructure. Through these, organizations can optimize the use of AI and develop new opportunities for growth and innovation in the digital world.

[dhirajmarketresearch]

[delightfullyatomiccollector-blog]

https://www.whatech.com/og/markets-research/industrial/918932-data-center-gpu-market-growth-in-the-us-opportunities-and-industry-analysis-from-2023-to-2028.html

Accelerating AI workloads and driving the demand for GPUs across US data centers to support cloud services, machine learning, and high-performance computing applications.

The US data center GPU market is growing at a very high rate. Its growth is attributed to the accelerated adoption of AI, ML, and HPC in several sectors.

[cybersecurityict]

Exascale Computing Market Size, Share, Analysis, Forecast, and Growth Trends to 2032: The Race to One Quintillion Calculations Per Second

The Exascale Computing Market was valued at USD 3.47 billion in 2023 and is expected to reach USD 29.58 billion by 2032, growing at a CAGR of 26.96% from 2024-2032.

The Exascale Computing Market is undergoing a profound transformation, unlocking unprecedented levels of computational performance. With the ability to process a billion billion (quintillion) calculations per second, exascale systems are enabling breakthroughs in climate modeling, genomics, advanced materials, and national security. Governments and tech giants are investing aggressively, fueling a race for exascale dominance that’s reshaping industries and redefining innovation timelines.

Exascale Computing Market revolutionary computing paradigm is being rapidly adopted across sectors seeking to harness the immense data-crunching potential. From predictive simulations to AI-powered discovery, exascale capabilities are enabling new frontiers in science, defense, and enterprise. Its impact is now expanding beyond research labs into commercial ecosystems, paving the way for smarter infrastructure, precision medicine, and real-time global analytics.

Get Sample Copy of This Report: https://www.snsinsider.com/sample-request/6035 

Market Keyplayers:

Hewlett Packard Enterprise (HPE) [HPE Cray EX235a, HPE Slingshot-11]

International Business Machines Corporation (IBM) [IBM Power System AC922, IBM Power System S922LC]

Intel Corporation [Intel Xeon Max 9470, Intel Max 1550]

NVIDIA Corporation [NVIDIA GH200 Superchip, NVIDIA Hopper H100]

Cray Inc. [Cray EX235a, Cray EX254n]

Fujitsu Limited [Fujitsu A64FX, Tofu interconnect D]

Advanced Micro Devices, Inc. (AMD) [AMD EPYC 64C 2.0GHz, AMD Instinct MI250X]

Lenovo Group Limited [Lenovo ThinkSystem SD650 V3, Lenovo ThinkSystem SR670 V2]

Atos SE [BullSequana XH3000, BullSequana XH2000]

NEC Corporation [SX-Aurora TSUBASA, NEC Vector Engine]

Dell Technologies [Dell EMC PowerEdge XE8545, Dell EMC PowerSwitch Z9332F]

Microsoft [Microsoft Azure NDv5, Microsoft Azure HPC Cache]

Amazon Web Services (AWS) [AWS Graviton3, AWS Nitro System]

Sugon [Sugon TC8600, Sugon I620-G30]

Google [Google TPU v4, Google Cloud HPC VM]

Alibaba Cloud [Alibaba Cloud ECS Bare Metal Instance, Alibaba Cloud HPC Cluster]

Market Analysis The exascale computing landscape is characterized by high-stakes R&D, global governmental collaborations, and fierce private sector competition. With countries like the U.S., China, and members of the EU launching national initiatives, the market is shaped by a mix of geopolitical strategy and cutting-edge technology. Key players are focusing on developing energy-efficient architectures, innovative software stacks, and seamless integration with artificial intelligence and machine learning platforms. Hardware giants are partnering with universities, startups, and defense organizations to accelerate deployments and overcome system-level challenges such as cooling, parallelism, and power consumption.

Market Trends

Surge in demand for high-performance computing in AI and deep learning

Integration of exascale systems with cloud and edge computing ecosystems

Government funding and national strategic investments on the rise

Development of heterogeneous computing systems (CPUs, GPUs, accelerators)

Emergence of quantum-ready hybrid systems alongside exascale architecture

Adoption across healthcare, aerospace, energy, and climate research sectors

Market Scope

Supercomputing for Scientific Discovery: Empowering real-time modeling and simulations at unprecedented speeds

Defense and Intelligence Advancements: Enhancing cybersecurity, encryption, and strategic simulations

Precision Healthcare Applications: Supporting drug discovery, genomics, and predictive diagnostics

Sustainable Energy Innovations: Enabling complex energy grid management and fusion research

Smart Cities and Infrastructure: Driving intelligent urban planning, disaster management, and IoT integration

As global industries shift toward data-driven decision-making, the market scope of exascale computing is expanding dramatically. Its capacity to manage and interpret massive datasets in real-time is making it essential for competitive advantage in a rapidly digitalizing world.

Market Forecast The trajectory of the exascale computing market points toward rapid scalability and broader accessibility. With increasing collaborations between public and private sectors, we can expect a new wave of deployments that bridge research and industry. The market is moving from proof-of-concept to full-scale operationalization, setting the stage for widespread adoption across diversified verticals. Upcoming innovations in chip design, power efficiency, and software ecosystems will further accelerate this trend, creating a fertile ground for startups and enterprise adoption alike.

Access Complete Report: https://www.snsinsider.com/reports/exascale-computing-market-6035 

Conclusion Exascale computing is no longer a vision of the future—it is the powerhouse of today’s digital evolution. As industries align with the pace of computational innovation, those embracing exascale capabilities will lead the next wave of transformation. With its profound impact on science, security, and commerce, the exascale computing market is not just growing—it is redefining the very nature of progress. Businesses, researchers, and nations prepared to ride this wave will find themselves at the forefront of a smarter, faster, and more resilient future.

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[technonews-biz]

GMI Cloud is building a new GPU infrastructure

The boom in artificial intelligence has created a huge demand for graphics processing units (GPUs). As many enterprises are looking to integrate artificial intelligence technologies into their systems, GPU infrastructure providers help them get access to the chips they need.

Cloud infrastructure

GMI Cloud, a San Jose-based startup that provides GPU cloud infrastructure, raised 82 million dollars in a Series A led by Headline Asia and strategic investors such as Banpu, a Thailand-based energy company, and Wistron, a Taiwan-based electronics company. Banpu will offer GMI Cloud capacity, while Wistron will develop products with the startup. The strategic partnership expands the company's ability to meet the growing global demand for GPUs, GMI Cloud founder and CEO Alex Ye told TechCrunch. The investment round, which brings the total capital raised to 93 mln dollars, consists of 15 mln dollars in equity and 67 mln dollars in debt financing.

Company launch

The company, which launched in 2022, started as a data center focused on providing Bitcoin compute node services. In an exclusive interview with TechCrunch, Ye said he noticed a growing demand for GPU computing power from investors and customers, and in response, shifted the company's focus to cloud-based artificial intelligence infrastructure.

Ye said the two-year-old startup already serves dozens of customers, including those in healthcare, research and telecommunications. The corporation plans to use the funding to build a new data center in Colorado. The facility will be needed to expand the company's capacity in North America and will complement existing data centers in Taiwan, Thailand and Malaysia. The company also plans to expand to 60-70 employees by the end of the year. The startup now has 35 employees in Asia and 18 in the US.

According to a recent McKinsey report, artificial intelligence could bring about 13 trillion dollars to the economy by 2030, of which the industrial sector will account for about 1 trillion dollars. According to a report by Grand View Research, the global artificial intelligence market will reach 1.8 trillion dollars by 2030.

Cloud processor vendors

GMI Cloud is not the only cloud GPU vendor. It competes with Coreweave, Nebius, Google Cloud's Vertex AI and major tech companies. Ye told TechCrunch that GMI Cloud differentiates itself from competitors with features such as customizable private cloud services and native support for Nvidia NIM, which simplifies integration with Nvidia hardware and software. He also noted that the company has a team of top-notch artificial intelligence engineers and high-performance computing (HPC) experts with experience in GoogleX, Alibaba Cloud and Supermicro.

“Our team has more than 20 years of experience in artificial intelligence and high-performance computing,” said Ye, who has 33 patents in artificial intelligence and extensive experience in building large-scale distributed systems. “GMI also offers professional artificial intelligence consulting services, helping enterprises train, customize and scale models, which is rarely offered by competitors.”

Cost-effective solution

GMI offers a cost-effective solution that provides optimized performance and resource management over competitors, supporting enterprises with end-to-end solutions from GPU hardware to artificial intelligence applications, Ye emphasized.

“In addition, we have a significant supply chain advantage by purchasing directly from manufacturers, allowing us to maintain a cost-effective and highly reliable supply chain,” Ye continued. “In addition, GMI is the only cloud service provider in Taiwan certified by Nvidia under the NCP/NPN program, further strengthening our competitive advantage in providing premium cloud services.”