#Optane persistent memory | Explore Tumblr posts and blogs

renatoferreiradasilva · 10 days ago

Text

RELATÓRIO CONSOLIDADO – INTEL CORPORATION PERSIST-X: Arquitetura Modular Persistente com Geometria Hexagonal Computacional para Memória Unificada Pós-Optane

Data: 30 de Junho de 2025 Destinatário: Intel Corporation – Divisão de Pesquisa em Memória e Armazenamento (MSD) Remetente: Consultoria Técnico-Científica Independente – Renato Ferreira da Silva

🧠 1. Contexto e Justificativa

A partir da análise crítica dos documentos técnicos:

Intel's Optane Memory: Revolutionising Data Storage with 3D XPoint Technology;

Performance Analysis of 3D XPoint SSDs in Virtualized and Non-Virtualized Environments (Zhang et al., 2018)

constatamos que o Optane falhou não por limitações físicas absolutas, mas por:

Má integração entre hardware e software;

Baixo desempenho térmico sob uso intensivo;

Arquitetura híbrida sem romper a hierarquia RAM–SSD;

Design de produto desalinhado com as necessidades emergentes de edge computing e AI persistente.

📍 2. Formulação do Problema-Mestre

Foi proposto um Problema Científico e de Engenharia de Alto Nível com o seguinte objetivo:

Determinar a geometria física, térmica e lógica ideal de um bloco cúbico hexagonal persistente, com capacidade de substituir HDDs e SSDs em sistemas como o Cyberdata NAS, respeitando limites de volume, consumo e latência, e permitindo escalabilidade modular.

🧩 3. Estrutura da Solução: PERSIST-X

3.1 Design Físico

Geometria Externa: Prisma hexagonal, 4.8 cm de aresta × 4.2 cm de altura (volume = 105 cm³).

Geometria Interna: Malha Weaire–Phelan modificada, com 5.760 células funcionais (híbridas entre armazenamento e computação).

Capacidade total útil: 92 TB por bloco.

3.2 Materiais

Estrutura: Compósito Cu–Al₂O₃

Substrato: SiC (alta condutividade térmica)

Dissipação:

Grafeno nanoporoso (vias verticais)

Microbombas piezoelétricas (resfriamento ativo)

🧪 4. Modelagem e Simulação

4.1 Simulação Térmica

Software: COMSOL Multiphysics

Equação resolvida:∇⋅(−κ∇T)=qv−ρCpv⋅∇T

Resultados:

ΔT < 15°C sob carga de 14 W

T_max = 63 °C com ambiente de 65 °C

4.2 Latência e Roteamento

Arquitetura: Router Mesh 6×6 com clusters de 64 células

Interface: CXL 2.0

Total end-to-end latency: 45 ns (com 22 ns de roteamento lógico e 0.4 ns/mm em enlace fotônico)

📈 5. Função de Custo Computacional

Com:

V=105 cm3, E=14 W, κ=1.800 W/mK

Lmeˊdia=45 ns, R=6.57 TB/W, Tmeˊdia=58∘C

Função:C(V,E,κ)=456.57+0.1⋅58=12.65

🧪 6. Prototipagem e Validação

Mockup NAS Modular

9 blocos PERSIST-X interconectados

Capacidade total: 828 TB útil

Interface: backplane CXL + barramento óptico

Throughput projetado: ≥ 98 GB/s por bloco

📚 7. Extensões e Aplicações

SetorAplicaçãoEdge AIInferência persistente sob baixa energiaDefesaComputação redundante em ambientes extremosFinançasLogs imutáveis e ultra rápidosMedicinaDispositivos diagnósticos que não perdem estadoCloudArmazenamento denso e escalável com baixa latência

🌐 8. Proposta de Caminho Estratégico

Fase 1 (2025)

Lançar iniciativa “PERSIST-X @ Intel Labs”

Criar consórcio com Samsung, DARPA, universidades (ETH, MIT, USP)

Fase 2 (2026–2027)

Construir protótipos TRL-4

Integrar com kernel Linux e Redis de modo persistente

Fase 3 (2028–2029)

Produção escalável

Incorporação em linhas como Optane Next ou CyberBrick

🏆 9. Proposta de Desafio Científico

HexaCompute Challenge 2025

Prêmio: US$ 1 milhão

Objetivo: Criar o melhor bloco persistente modular hexagonal

Categorias: Simulação física, prova de conceito, arquitetura computacional

Parceiros sugeridos: CERN, Intel, Open Compute Project, DARPA Microsystems, TSMC, Google

✍️ 10. Assinatura Técnica e Contato

Renato Ferreira da Silva pesquisador independente ORCID: 0009-0003-8908-481X [email protected]

0 notes

skywardtelecom · 10 days ago

Text

What are the top 5 enterprise level servers from Dell?

Here are Dell's top 5 enterprise-level servers for 2025, based on performance, scalability, and industry relevance.

1. Dell PowerEdge R940xa

Performance: A 4U rack server designed for compute-intensive workloads like AI, machine learning, and GPU-accelerated databases. It supports up to four 2nd Gen Intel Xeon Scalable processors (112 cores) and up to 4 double-width GPUs (e.g., NVIDIA A100) or 8 FPGAs .

Memory & Storage: Features 48 DDR4 DIMM slots (up to 6 TB) with support for NVDIMMs and Intel Optane DC persistent memory, totaling 15.36 TB. Internal storage includes up to 32x 2.5" drives (132 TB) and 4 NVMe PCIe SSDs .

Management: Built-in iDRAC9 with lifecycle controller for remote management and encrypted firmware updates .

2. Dell PowerEdge XE9680

AI/HPC Focus: A 4U server optimized for AI training and high-performance computing. It integrates dual Intel Xeon Platinum 8468 CPUs and supports up to 8 NVIDIA H100 or AMD MI300X GPUs with NVLink for extreme parallel processing .

Scalability: Offers 12x PCIe Gen 5 slots, 1 TB DDR4 memory, and high-speed NVMe storage for real-time data processing. Its liquid-cooled variant (XE9680L) enhances efficiency in dense data centers .

Security: Cyber-resilient architecture with silicon root of trust and secure erase .

3. Dell PowerEdge R750xs

Flexibility: A 2U rack server ideal for virtualization, cloud, and ERP systems. It supports 3rd Gen Intel Xeon Silver/Gold processors (up to 32 cores) and 16 DDR4 DIMM slots (1 TB max) .

Storage: Configurable with up to 24x 2.5" SAS/SATA drives or 16x NVMe drives, plus rear expansion for additional 2.5" drives. Features PCIe Gen 4 slots for GPU/FPGA acceleration .

Efficiency: Air-cooled design with optional direct liquid cooling (DLC) for power optimization .

4. Dell PowerEdge R640

Density & Cost-Efficiency: A 1U dual-socket server designed for dense data centers. It supports 2nd Gen Intel Xeon Scalable processors and up to 24x 2.5" drives (132 TB) or 10x NVMe drives for software-defined storage (SDS) .

Networking: Offers 12x PCIe Gen 3 slots and 10/25/100 GbE connectivity, making it suitable for private cloud and HPC workloads .

Management: Agent-free iDRAC9 and OpenManage Enterprise for centralized monitoring .

5. Dell PowerEdge R840

Multiprocessing: A 2U 4-socket server for data analytics and large-scale databases. It supports up to four Intel Xeon Scalable processors (112 cores) and 48 DDR4 DIMMs (6 TB) .

Storage: Configurable with up to 26x 2.5" drives (184 TB) or 24x NVMe drives (153 TB), plus 2x rear 2.5" drives. Supports dual FPGAs or GPUs for acceleration .

Security: System lockdown mode and cryptographically signed firmware to prevent unauthorized changes .

Honorable Mentions:

Dell PowerEdge R6715 (1U, AMD EPYC 9005 series): Optimized for AI inference and edge computing, with up to 64 cores and 1.5 TB DDR5 memory . Dell PowerEdge R7715 (2U, single-socket): High-performance server for data warehousing, supporting up to 160 cores and 6 TB DDR5 memory .

These servers are selected based on their ability to handle modern enterprise workloads, scalability, and Dell’s ongoing innovation in AI, security, and management tools. For specific use cases (e.g., edge vs. core data center), consult Dell’s latest documentation or partner with a certified provider.

#dell #r760 #server

0 notes

skyfallights · 12 days ago

Text

3D XPoint Technology Market Share Redefining High-Speed Data Storage for the Digital Era

The 3D XPoint Technology Market Share is gaining momentum as industries increasingly demand ultra-fast, non-volatile memory solutions that bridge the performance gap between DRAM and NAND flash. Developed jointly by Intel and Micron, 3D XPoint delivers exceptional speed, endurance, and low latency—revolutionizing storage architecture in data centers, AI workloads, and enterprise computing.

According to Market Share Research Future, the global 3D XPoint technology market is expected to reach USD 7.5 billion by 2030, growing at a robust CAGR of 13.3% during the forecast period. As the world generates and processes data at unprecedented speeds, the adoption of 3D XPoint is set to rise, driven by advancements in artificial intelligence, big data analytics, and cloud infrastructure.

Market Share Overview

3D XPoint (pronounced “cross point”) is a next-generation memory technology that provides persistent storage with performance closer to DRAM and endurance far superior to NAND flash. It is designed to store data in a three-dimensional matrix and can switch states up to 1,000 times faster than traditional flash memory.

This disruptive memory architecture is addressing the bottlenecks associated with latency, durability, and scalability in modern computing systems. Its ability to support high-speed random read/write access and endure millions of cycles makes it ideal for performance-intensive applications like real-time data processing, AI inference, and in-memory computing.

Enhanced Market Share Segmentation

By Type:

Standalone Memory

Used in SSDs, expansion cards

Storage-Class Memory (SCM)

Blends memory and storage into a single tier

Embedded Memory

By Application:

Enterprise Storage

Data Centers

Consumer Electronics

Automotive Electronics

Healthcare Devices

Industrial IoT Systems

By End-User:

IT & Telecom

BFSI

Healthcare

Automotive

Government

Retail & E-Commerce

By Region:

North America – Dominates the market due to early adoption of advanced memory technologies

Europe – Growth fueled by cloud computing and enterprise digitization

Asia-Pacific – Fastest-growing region, led by semiconductor manufacturing and consumer electronics demand

Rest of the World – Emerging interest in AI and defense applications

Key Trends Influencing Growth

Integration with AI and Machine Learning Workloads: The high throughput and low latency of 3D XPoint make it well-suited for AI models that require rapid data movement and decision-making.

Edge Computing Adoption: With the rise of real-time data processing at the edge, 3D XPoint is being considered for latency-sensitive environments such as autonomous vehicles and smart cities.

Hybrid Storage Architectures: Enterprises are integrating 3D XPoint with DRAM and SSDs to optimize storage hierarchies and reduce total cost of ownership.

In-Memory Databases (IMDB): 3D XPoint boosts performance in databases requiring immediate access to vast amounts of data, such as SAP HANA or Oracle Database.

Rise of Optane Products: Intel’s Optane SSDs and memory modules, powered by 3D XPoint, are gaining traction across high-performance computing markets.

Segment Insights

Standalone Memory

Standalone memory devices using 3D XPoint, such as NVMe-based SSDs, are in high demand across enterprise IT infrastructures. They offer faster boot times, application load speeds, and overall system responsiveness compared to traditional SSDs.

Storage-Class Memory (SCM)

SCM combines the benefits of DRAM and NAND flash. It enables faster storage with persistent memory capabilities, allowing systems to resume instantly and retain data without power. Adoption is rising in hyperscale data centers and mission-critical applications.

Consumer Electronics

3D XPoint is beginning to appear in high-end laptops, gaming PCs, and workstations where users seek faster load times and improved multitasking capabilities.

End-User Insights

IT & Telecom

Data centers supporting 5G, virtualization, and software-defined storage benefit significantly from 3D XPoint’s low latency and endurance. Service providers are using it to reduce response times and improve service-level agreements (SLAs).

BFSI Sector

Banks and financial institutions require real-time analytics and fraud detection. 3D XPoint supports these functions by enabling faster access to massive datasets, driving improved customer experiences and compliance.

Healthcare

Medical imaging, diagnostics, and health record processing demand rapid, secure storage solutions. 3D XPoint ensures faster retrieval of critical patient data, reducing delays in clinical workflows.

Automotive

In autonomous vehicles and infotainment systems, 3D XPoint’s resilience and high speed enhance safety and performance. Its ability to function reliably under extreme conditions makes it ideal for automotive-grade applications.

Key Players

The 3D XPoint technology ecosystem is currently limited to a few key players, with others entering the domain through partnerships and acquisitions:

Intel Corporation

Micron Technology Inc.

Western Digital Technologies

Samsung Electronics Co., Ltd.

SK hynix Inc.

Hewlett Packard Enterprise (HPE)

IBM Corporation

Dell Technologies

These companies are investing in R&D to expand the use cases of 3D XPoint, reduce costs, and integrate the technology into mainstream computing platforms.

Future Outlook

The future of 3D XPoint technology lies in its ability to disrupt memory and storage hierarchies. As edge computing, AI, and cloud-native workloads proliferate, the demand for fast, durable, and persistent memory will continue to rise.

With decreasing production costs, expanding supply chains, and broader application scopes, 3D XPoint is expected to become a core component of future computing architectures. Organizations that prioritize performance, endurance, and data integrity will increasingly migrate toward hybrid solutions powered by 3D XPoint.

Trending Report Highlights

Explore emerging technologies transforming the semiconductor and intelligent systems landscape:

Embedded Display Market Share

Embedded Subscriber Identity Module Market Share

Enterprise Manufacturing Intelligence Market Share

Ethernet Adapter Market Share

Robotic Refueling System Market Share

Roll To Roll Printing Market Share

Rugged IC Market Share

Single Mode Optical Fiber Market Share

Smart Motor Market Share

Smart Wiring Device Market Share

Sound Reinforcement Market Share

0 notes

allaboutkeyingo · 22 days ago

Text

Windows 11 Pro VS Pro For Workstation

Windows 11 Pro and Windows 11 Pro for Workstations are both professional-grade operating systems, but they cater to different user needs. Here’s a detailed comparison:

1. Target Audience

Windows 11 Pro: Designed for general business users, professionals, and power users who need advanced features like BitLocker, Remote Desktop, and Hyper-V.

Windows 11 Pro for Workstations: Optimized for high-end workstations, such as engineers, data scientists, and creative professionals who require extreme performance and reliability for demanding workloads.

2. Hardware Support

Windows 11 Pro:

Supports up to 2 CPUs (sockets).

Maximum 128 cores.

Up to 2TB RAM (64-bit).

Windows 11 Pro for Workstations:

Supports up to 4 CPUs (sockets).

Maximum 128 cores.

Up to 6TB RAM (64-bit).

Non-Volatile DIMM (NVDIMM) support for persistent memory.

3. File System & Performance

Windows 11 Pro:

Uses NTFS (standard file system).

Windows 11 Pro for Workstations:

Includes ReFS (Resilient File System) for better data integrity and fault tolerance.

Microsoft’s SMB Direct (RDMA support) for faster network file transfers.

Persistent memory (NVDIMM-N) support for ultra-fast storage.

4. Storage & Reliability

Windows 11 Pro for Workstations includes:

Storage Spaces Direct (Software-defined storage clustering).

Faster file handling with ReFS (self-healing capabilities).

Better support for high-speed storage (NVMe, Optane).

5. Networking

Windows 11 Pro for Workstations supports:

SMB Direct (for low-latency, high-throughput networking).

Improved handling of large file transfers (useful for media production, CAD, and scientific computing).

6. Pricing & Licensing

Windows 11 Pro: Typically cheaper, suitable for most business users. ($35 at Keyingo.com)

Windows 11 Pro for Workstations: More expensive, aimed at enterprise and high-performance computing. ($40 at Keyingo.com)

Which One Should You Choose?

Choose Windows 11 Pro if:

You need standard business features (BitLocker, Hyper-V, Remote Desktop).

You don’t require extreme hardware support.

You’re using typical office or development workloads.

Choose Windows 11 Pro for Workstations if:

You need 4 CPU support or 6TB RAM.

You work with high-performance storage (NVMe, NVDIMM).

You need ReFS or SMB Direct for large-scale data processing.

You’re running CAD, 3D rendering, scientific simulations, or AI workloads.

Final Verdict

Most users will be fine with Windows 11 Pro.

Workstation users (engineers, researchers, media professionals) should consider Pro for Workstations for its expanded hardware support and advanced file systems.

#Windows 11 Pro VS Pro For Workstation #Windows 11 Pro VS Windows 11 Pro For Workstation #Compare Windows 11 Pro and windows 11 Pro For Workstation

1 note · View note

semiindustry · 23 days ago

Text

Next-Gen Memory in Data Centers: Enhancing Speed and Reducing Power Consumption

As data centers become the backbone of modern digital infrastructure, the need for faster and more energy-efficient memory has never been more critical. With workloads driven by AI, big data analytics, cloud computing, and real-time applications, traditional memory technologies like DRAM and NAND flash are struggling to meet the growing performance and efficiency demands. This has fueled the adoption of next-generation memory technologies—including MRAM (Magnetoresistive RAM), ReRAM (Resistive RAM), PCM (Phase-Change Memory), and 3D XPoint—in data centers worldwide.

Download PDF Brochure @ https://www.marketsandmarkets.com/pdfdownloadNew.asp?id=632

One of the primary advantages of next-gen memory in data centers is the significant improvement in data access speed. Traditional DRAM offers fast access but is volatile and energy-intensive, while NAND flash provides persistence but suffers from latency and limited endurance. Next-gen memory fills this performance gap by combining the speed of DRAM with the persistence of flash. For instance, Intel’s Optane (based on 3D XPoint technology) delivers near-DRAM speeds while retaining data without power. This enables data centers to accelerate database processing, reduce boot times, and support high-performance computing tasks without frequent memory refresh cycles.

Power consumption is another major concern in large-scale data centers, where memory can account for a significant portion of total energy use. Unlike DRAM, which requires constant power to retain data, next-gen memory technologies are non-volatile, meaning they retain information even when the power is off. This results in substantial energy savings during idle periods or power-down cycles. MRAM and ReRAM, for example, consume far less static power than DRAM, making them ideal for low-energy server environments and green data center initiatives.

Next-gen memory also enables higher density and scalability, which is essential as data centers expand to handle massive workloads. Phase-Change Memory and ReRAM offer multi-level cell storage capabilities, allowing more data to be stored in a smaller footprint. This density not only reduces the physical size of memory modules but also lowers cooling requirements, further decreasing overall power consumption and operational costs.

In-memory computing, a key trend in modern data center architecture, also benefits from the integration of next-gen memory. By allowing processing to occur directly within or close to the memory itself, technologies like PCM and ReRAM eliminate the need for constant data movement between the CPU and memory. This reduces latency, accelerates processing speed, and improves system efficiency—particularly in AI training, financial modeling, and real-time analytics.

Furthermore, next-gen memory enhances data durability and system reliability. Unlike NAND flash, which degrades over time with repeated writes, MRAM and PCM offer high endurance, making them suitable for write-intensive applications such as transaction processing, caching, and logging. This durability extends the lifespan of memory hardware, reducing maintenance costs and increasing data center uptime.

In conclusion, next-generation memory technologies are playing a pivotal role in transforming data center performance. By delivering faster data access, reducing power consumption, and enabling higher density storage, these advanced memory solutions are addressing the limitations of traditional architectures. As data centers continue to scale and evolve to support the digital economy, the integration of next-gen memory will be crucial to achieving greater efficiency, reliability, and sustainability.

#next generation memory

0 notes

san-storage-blog · 3 months ago

Text

Accelerating Data Flow in Modern SAN Solution Environments

The demand for efficient, high-speed data transfer has skyrocketed in response to growing data-intensive applications such as AI, cloud computing, and big data analytics. To keep up, modern Storage Area Network (SAN) environments must evolve, enabling businesses to maintain seamless operations without bottlenecks or downtime.

This post explores how to accelerate data flow in SAN environments by leveraging cutting-edge technologies, optimized architectures, and tailored best practices. Whether you're an IT professional seeking to enhance your organization's data infrastructure or a data center manager looking for performance gains, this guide is for you.

Why Accelerating Data Flow in SANs Matters

The storage landscape today is vastly different from what it was a decade ago. Enterprises now contend with multi-petabyte data requirements, real-time analytics needs, and globally distributed teams requiring instant, secure access.

Accelerating data flow in SAN environments is critical because it directly impacts the following areas:

Performance for latency-sensitive applications like AI and machine learning.

Business continuity, as slower data transfer can lead to missed SLAs and reduced customer satisfaction.

Scalability, ensuring the infrastructure can meet future demands without performance trade-offs.

Without proper focus on speeding up SAN communication, organizations may face prolonged transfer times, higher latency, and inefficiencies that negatively affect services.

Key Challenges in Modern SAN Environments

Before we explore the solutions, it’s vital to understand the common challenges that modern SAN environments face when it comes to data flow.

1. Latency Bottlenecks

With the surge in remote access and 24/7 services, reducing latency is paramount. Traditional SAN solutions relying on aging hardware or slow interconnects often serve as a chokepoint in data transmission.

2. High Workload Diversity

Enterprise workloads are more diverse than ever, spanning transactional databases, analytics, AI training, and high-volume media files. Traditional, one-size-fits-all SAN architectures struggle to meet all these varying demands with precision performance.

3. Network Congestion

Aging or inadequately managed Fibre Channel or Ethernet fabrics can result in unnecessary packet loss, retransmissions, and slower overall performance.

4. Capacity Management

Modern SAN environments require designs that balance vast storage capacity with high-speed retrieval, but mismatched configurations can bog down data flow.

Strategies for Accelerating Data Flow in SAN Environments

The following strategies leverage advanced technologies and best practices to address challenges and enable faster, more reliable data transfer.

1. Upgrade to NVMe-oF (Non-Volatile Memory Express over Fabrics)

Switching to NVMe-oF in SAN architectures significantly reduces latency by optimizing the protocol layer for flash storage. NVMe-oF eliminates inefficiencies found in traditional SCSI interfaces by providing direct, high-speed communication between hosts and storage.

Why it matters: NVMe-oF offers concurrent, multi-queue support, enabling faster data access even under heavy workloads.

Use case: Enterprises running latency-critical applications, like AI model training or real-time transaction processing, experience significant benefits.

2. Implement Advanced Caching Solutions

Utilizing server-side or storage-based caching solutions can greatly enhance read/write performance. Modern caching systems use DRAM or even persistent memory like Intel Optane to temporarily store frequently accessed data closer to compute resources.

Why it matters: Reduces repetitive I/O operations for commonly used datasets, accelerating overall data retrieval.

Best practice: Pair caching solutions with predictive algorithms to ensure the right data is cached based on workload requirements.

3. Leverage Automated Storage Tiering

Tiered storage solutions automatically allocate data across different storage types based on performance needs. Frequently accessed data (hot data) is placed on high-performance flash, while rarely accessed data (cold data) is moved to HDDs or archival storage.

Why it matters: Improves cost-efficiency without sacrificing performance.

Example: A hybrid SAN employing all-flash arrays for high-priority workloads and slower magnetic storage for archiving creates an ideal balance.

4. Optimize Your Fabric Infrastructure

Advanced fabric technologies such as Fibre Channel Gen 6 and Ethernet-based RDMA (Remote Direct Memory Access) dramatically reduce network congestion. RDMA, in particular, bypasses CPU processing for network data, increasing throughput.

Why it matters: Faster interconnects facilitate seamless communication between SAN nodes, significantly boosting performance.

Pro tip: Regularly monitor fabric performance and use QoS (Quality of Service) policies to prioritize critical workloads.

5. Employ AI/ML for Intelligent SAN Management

AI-powered SAN management tools offer real-time performance analytics and proactive anomaly detection. By identifying potential bottlenecks and automatically redistributing workloads, these tools optimize SAN operations dynamically.

Why it matters: AI ensures that system performance remains consistent across changing workloads and infrastructure demands.

6. Use Compression and Deduplication Wisely

Data compression and deduplication technologies in SAN environments free up precious bandwidth and storage by reducing the volume of duplicate or redundant data being processed.

Why it matters: Leads to faster writes and extended storage capacity without compromising performance.

When to use: For environments with high data redundancy, such as backup systems or content repositories.

Real-World Impact of Accelerating Data Flow

Case Study: Optimizing an eCommerce Platform

An eCommerce enterprise handling millions of daily transactions faced slow order processing and higher cart abandonment due to SAN-related performance bottlenecks. After implementing NVMe-oF alongside a state-of-the-art RDMA fabric, processing times dropped by 30%, delivering seamless customer experiences and boosting revenue by 15%.

Case Study 2: Enhancing Data Analytics Timelines

A financial services firm reduced big data processing timelines by 40% by deploying automated storage tiering and caching solutions. Thanks to lower retrieval times, the firm gained faster access to insights, supporting better decision-making.

Best Practices for Maintaining High-Speed SAN Environments

Regular Performance Reviews: Continuously monitor latency, throughput, and IOPS (Input/Output Operations Per Second).

Upgrade Periodically: Stay ahead by upgrading hardware or software in line with evolving tech standards.

Establish Redundancy: Ensure your SAN design includes redundancy to handle unexpected node failures without affecting performance.

Train Personnel: Equip your IT teams with the latest knowledge to manage evolving SAN technologies effectively.

Unlock Your SAN’s True Potential

The evolution of modern SAN environments presents an exciting opportunity for IT professionals and enterprises to unlock unprecedented performance levels. From adopting NVMe-oF to leveraging AI-driven insights, there are countless ways to improve data flow efficiency and achieve better business outcomes.

Want to explore how advanced SAN solution technologies can transform your organization? Implement these best practices, and let your data center thrive.

#storage

0 notes

differenttimemachinecrusade · 4 months ago

Text

In-Memory Computing Market Landscape: Opportunities and Competitive Insights 2032

The In-Memory Computing Market was valued at USD 10.9 Billion in 2023 and is expected to reach USD 45.0 Billion by 2032, growing at a CAGR of 17.08% from 2024-2032

The in-memory computing (IMC) market is experiencing rapid expansion, driven by the growing demand for real-time data processing, AI, and big data analytics. Businesses across industries are leveraging IMC to enhance performance, reduce latency, and accelerate decision-making. As digital transformation continues, organizations are adopting IMC solutions to handle complex workloads with unprecedented speed and efficiency.

The in-memory computing market continues to thrive as enterprises seek faster, more scalable, and cost-effective solutions for managing massive data volumes. Traditional disk-based storage systems are being replaced by IMC architectures that leverage RAM, flash memory, and advanced data grid technologies to enable high-speed computing. From financial services and healthcare to retail and manufacturing, industries are embracing IMC to gain a competitive edge in the era of digitalization.

Get Sample Copy of This Report: https://www.snsinsider.com/sample-request/3570

Market Keyplayers:

SAP SE – SAP HANA

IBM – IBM Db2 with BLU Acceleration

Microsoft – Azure SQL Database In-Memory

Oracle Corporation – Oracle TimesTen In-Memory Database

Intel – Intel Optane DC Persistent Memory

Microsoft – SQL Server In-Memory OLTP

GridGain Systems – GridGain In-Memory Computing Platform

VMware – VMware vSphere with Virtual Volumes

Amazon Web Services (AWS) – Amazon ElastiCache

Pivotal Software – Pivotal GemFire

TIBCO Software Inc.– TIBCO ActiveSpaces

Redis Labs – Redis Enterprise

Hazelcast – Hazelcast IMDG (In-Memory Data Grid)

Cisco – Cisco In-Memory Analytics

Qlik – Qlik Data integration

Market Trends Driving Growth

1. Rising Adoption of AI and Machine Learning

The increasing use of artificial intelligence (AI) and machine learning (ML) applications is fueling the demand for IMC solutions. AI-driven analytics require real-time data processing, making IMC an essential component for businesses leveraging predictive insights and automation.

2. Growing Demand for Real-Time Data Processing

IMC is becoming a critical technology in industries where real-time data insights are essential. Sectors like financial services, fraud detection, e-commerce personalization, and IoT-driven smart applications are benefiting from the high-speed computing capabilities of IMC platforms.

3. Integration with Cloud Computing

Cloud service providers are incorporating in-memory computing to offer faster data processing capabilities for enterprise applications. Cloud-based IMC solutions enable scalability, agility, and cost-efficiency, making them a preferred choice for businesses transitioning to digital-first operations.

4. Increased Adoption in Financial Services

The financial sector is one of the biggest adopters of IMC due to its need for ultra-fast transaction processing, risk analysis, and algorithmic trading. IMC helps banks and financial institutions process vast amounts of data in real time, reducing delays and improving decision-making accuracy.

5. Shift Toward Edge Computing

With the rise of edge computing, IMC is playing a crucial role in enabling real-time data analytics closer to the data source. This trend is particularly significant in IoT applications, autonomous vehicles, and smart manufacturing, where instant processing and low-latency computing are critical.

Enquiry of This Report: https://www.snsinsider.com/enquiry/3570

Market Segmentation:

By Components

Hardware

Software

Services

By Application

Fraud detection

Risk management

Real-time analytics

High-frequency trading

By Vertical

BFSI

Healthcare

Retail

Telecoms

Market Analysis and Current Landscape

Key factors contributing to this growth include:

Surging demand for low-latency computing: Businesses are prioritizing real-time analytics and instant decision-making to gain a competitive advantage.

Advancements in hardware and memory technologies: Innovations in DRAM, non-volatile memory, and NVMe-based architectures are enhancing IMC capabilities.

Increased data volumes from digital transformation: The exponential growth of data from AI, IoT, and connected devices is driving the need for high-speed computing solutions.

Enterprise-wide adoption of cloud-based IMC solutions: Organizations are leveraging cloud platforms to deploy scalable and cost-efficient IMC architectures.

Despite its strong growth trajectory, the market faces challenges such as high initial investment costs, data security concerns, and the need for skilled professionals to manage and optimize IMC systems.

Regional Analysis: Growth Across Global Markets

1. North America

North America leads the in-memory computing market due to early adoption of advanced technologies, significant investments in AI and big data, and a strong presence of key industry players. The region’s financial services, healthcare, and retail sectors are driving demand for IMC solutions.

2. Europe

Europe is witnessing steady growth in IMC adoption, with enterprises focusing on digital transformation and regulatory compliance. Countries like Germany, the UK, and France are leveraging IMC for high-speed data analytics and AI-driven business intelligence.

3. Asia-Pacific

The Asia-Pacific region is emerging as a high-growth market for IMC, driven by increasing investments in cloud computing, smart cities, and industrial automation. Countries like China, India, and Japan are leading the adoption, particularly in sectors such as fintech, e-commerce, and telecommunications.

4. Latin America and the Middle East

These regions are gradually adopting IMC solutions, particularly in banking, telecommunications, and energy sectors. As digital transformation efforts accelerate, demand for real-time data processing capabilities is expected to rise.

Key Factors Driving Market Growth

Technological Advancements in Memory Computing – Rapid innovations in DRAM, NAND flash, and persistent memory are enhancing the efficiency of IMC solutions.

Growing Need for High-Speed Transaction Processing – Industries like banking and e-commerce require ultra-fast processing to handle large volumes of transactions.

Expansion of AI and Predictive Analytics – AI-driven insights depend on real-time data processing, making IMC an essential component for AI applications.

Shift Toward Cloud-Based and Hybrid Deployments – Enterprises are increasingly adopting cloud and hybrid IMC solutions for better scalability and cost efficiency.

Government Initiatives for Digital Transformation – Public sector investments in smart cities, digital governance, and AI-driven public services are boosting IMC adoption.

Future Prospects: What Lies Ahead?

1. Evolution of Memory Technologies

Innovations in next-generation memory solutions, such as storage-class memory (SCM) and 3D XPoint technology, will further enhance the capabilities of IMC platforms, enabling even faster data processing speeds.

2. Expansion into New Industry Verticals

IMC is expected to witness growing adoption in industries such as healthcare (for real-time patient monitoring), logistics (for supply chain optimization), and telecommunications (for 5G network management).

3. AI-Driven Automation and Self-Learning Systems

As AI becomes more sophisticated, IMC will play a key role in enabling real-time data processing for self-learning AI models, enhancing automation and decision-making accuracy.

4. Increased Focus on Data Security and Compliance

With growing concerns about data privacy and cybersecurity, IMC providers will integrate advanced encryption, access control, and compliance frameworks to ensure secure real-time processing.

5. Greater Adoption of Edge Computing and IoT

IMC’s role in edge computing will expand, supporting real-time data processing in autonomous vehicles, smart grids, and connected devices, driving efficiency across multiple industries.

Access Complete Report: https://www.snsinsider.com/reports/in-memory-computing-market-3570

Conclusion

The in-memory computing market is witnessing rapid expansion as organizations embrace real-time data processing to drive innovation and competitive advantage. With the integration of AI, cloud computing, and edge technologies, IMC is set to revolutionize industries by enabling faster, more efficient decision-making. As advancements in memory technology continue, businesses that invest in IMC solutions will be well-positioned for the future of high-performance computing.

About Us:

SNS Insider is one of the leading market research and consulting agencies that dominates the market research industry globally. Our company's aim is to give clients the knowledge they require in order to function in changing circumstances. In order to give you current, accurate market data, consumer insights, and opinions so that you can make decisions with confidence, we employ a variety of techniques, including surveys, video talks, and focus groups around the world.

Jagney Dave - Vice President of Client Engagement

Phone: +1-315 636 4242 (US) | +44- 20 3290 5010 (UK)

The In-Memory Computing Market was valued at USD 10.9 Billion in 2023 and is expected to reach USD 45.0 Billion by 2032, growing at a CAGR of 17.08% from 2024-2032

Get Sample Copy of This Report: https://www.snsinsider.com/sample-request/3570

Market Keyplayers:

SAP SE – SAP HANA

IBM – IBM Db2 with BLU Acceleration

Microsoft – Azure SQL Database In-Memory

Oracle Corporation – Oracle TimesTen In-Memory Database

Intel – Intel Optane DC Persistent Memory

Microsoft – SQL Server In-Memory OLTP

GridGain Systems – GridGain In-Memory Computing Platform

VMware – VMware vSphere with Virtual Volumes

Amazon Web Services (AWS) – Amazon ElastiCache

Pivotal Software – Pivotal GemFire

TIBCO Software Inc.– TIBCO ActiveSpaces

Redis Labs – Redis Enterprise

Hazelcast – Hazelcast IMDG (In-Memory Data Grid)

Cisco – Cisco In-Memory Analytics

Qlik – Qlik Data integration

Market Trends Driving Growth

1. Rising Adoption of AI and Machine Learning

2. Growing Demand for Real-Time Data Processing

3. Integration with Cloud Computing

4. Increased Adoption in Financial Services

5. Shift Toward Edge Computing

Enquiry of This Report: https://www.snsinsider.com/enquiry/3570

Market Segmentation:

By Components

Hardware

Software

Services

By Application

Fraud detection

Risk management

Real-time analytics

High-frequency trading

By Vertical

BFSI

Healthcare

Retail

Telecoms

Market Analysis and Current Landscape

Key factors contributing to this growth include:

Surging demand for low-latency computing: Businesses are prioritizing real-time analytics and instant decision-making to gain a competitive advantage.

Advancements in hardware and memory technologies: Innovations in DRAM, non-volatile memory, and NVMe-based architectures are enhancing IMC capabilities.

Increased data volumes from digital transformation: The exponential growth of data from AI, IoT, and connected devices is driving the need for high-speed computing solutions.

Enterprise-wide adoption of cloud-based IMC solutions: Organizations are leveraging cloud platforms to deploy scalable and cost-efficient IMC architectures.

Regional Analysis: Growth Across Global Markets

1. North America

2. Europe

3. Asia-Pacific

4. Latin America and the Middle East

Key Factors Driving Market Growth

Technological Advancements in Memory Computing – Rapid innovations in DRAM, NAND flash, and persistent memory are enhancing the efficiency of IMC solutions.

Growing Need for High-Speed Transaction Processing – Industries like banking and e-commerce require ultra-fast processing to handle large volumes of transactions.

Expansion of AI and Predictive Analytics – AI-driven insights depend on real-time data processing, making IMC an essential component for AI applications.

Shift Toward Cloud-Based and Hybrid Deployments – Enterprises are increasingly adopting cloud and hybrid IMC solutions for better scalability and cost efficiency.

Government Initiatives for Digital Transformation – Public sector investments in smart cities, digital governance, and AI-driven public services are boosting IMC adoption.

Future Prospects: What Lies Ahead?

1. Evolution of Memory Technologies

2. Expansion into New Industry Verticals

3. AI-Driven Automation and Self-Learning Systems

As AI becomes more sophisticated, IMC will play a key role in enabling real-time data processing for self-learning AI models, enhancing automation and decision-making accuracy.

4. Increased Focus on Data Security and Compliance

With growing concerns about data privacy and cybersecurity, IMC providers will integrate advanced encryption, access control, and compliance frameworks to ensure secure real-time processing.

5. Greater Adoption of Edge Computing and IoT

IMC’s role in edge computing will expand, supporting real-time data processing in autonomous vehicles, smart grids, and connected devices, driving efficiency across multiple industries.

Access Complete Report: https://www.snsinsider.com/reports/in-memory-computing-market-3570

Conclusion

About Us:

Jagney Dave - Vice President of Client Engagement

Phone: +1-315 636 4242 (US) | +44- 20 3290 5010 (UK)

#in-memory computing market #in-memory computing market Analysis #in-memory computing market Scope #in-memory computing market growth #in-memory computing market trends

0 notes

computer8920 · 7 months ago

Text

The Future of Server RAM: Emerging Technologies and Trends

Server RAM is an essential component in data centers and cloud infrastructures, crucially ensuring speed, efficiency, and reliability in modern computing environments. As businesses increasingly rely on data-driven operations, the demand for advanced server RAM solutions is growing. This blog explores the future of server RAM, focusing on emerging technologies and trends shaping the industry.

Introduction to Server RAM

Server RAM (Random Access Memory) is a volatile memory that provides fast access to data for active processes. Unlike permanent storage like SSDs or HDDs, RAM enables rapid data retrieval, which is vital for server operations. Over time, server RAM has evolved to support larger capacities, faster speeds, and greater efficiency, addressing the growing demands of server workloads.

The Evolution of Server RAM

From DDR to DDR5: The Double Data Rate (DDR) series has been the standard for server memory. DDR4, introduced in 2014, improved upon DDR3 with higher densities and lower voltage, offering better performance with speeds starting at 2133 MT/s. DDR5, released in 2020, significantly enhances performance with double the bandwidth and density of DDR4, reaching speeds from 4800 MT/s to potentially 8400 MT/s. DDR5 also incorporates technologies like Decision Feedback Equalization (DFE) for improved signal integrity and reduced latency.

The Rise of Persistent Memory: Persistent memory, like Intel Optane, combines the speed of RAM with the non-volatility of storage. It retains data even during power outages, offering faster data access, enhanced data integrity, and cost efficiency. Persistent memory can act as an intermediate storage tier, improving performance without relying on expensive DRAM.

Emerging Technologies in Server RAM

DDR5 and Beyond: Research is already underway for future generations of DDR memory, such as DDR6, which are expected to offer higher speeds, efficiency, and error correction.

3D Stacking and High-Bandwidth Memory (HBM): 3D stacking and HBM technologies stack memory chips vertically, offering higher capacities in smaller footprints, increased bandwidth, and lower power consumption. These are ideal for data-intensive tasks like AI, machine learning, and high-performance computing.

Next-Generation Non-Volatile Memory Express (NVMe): NVMe, typically used for storage, is being integrated with memory technologies for low-latency, high-speed memory solutions. The combination of NVMe with persistent memory enhances performance and scalability in data centers.

Trends Shaping the Future of Server RAM

AI and Machine Learning: The rise of AI and ML demands faster, high-capacity server RAM to process large datasets quickly. Future RAM technologies must meet the high-performance requirements of these data-intensive applications.

Edge Computing: Edge computing, which processes data closer to the source of generation, requires memory that can handle real-time data processing. Technologies like HBM and persistent memory are well-suited for these environments, offering the necessary performance and efficiency in constrained spaces.

Data Center Optimization: As data centers grow, optimizing memory usage becomes crucial. Memory disaggregation, which separates memory from individual servers for central pooling, and composable infrastructure, which allows dynamic resource allocation, are key trends in improving efficiency and reducing costs.

Green Computing: Environmental sustainability is a key consideration. Innovations in low-power DDR and energy-efficient stacking technologies aim to reduce power consumption and create more sustainable data centers.

Challenges and Considerations

Compatibility and Integration: New memory technologies must seamlessly integrate with existing server architectures. Collaboration between memory manufacturers and vendors is vital to ensure smooth adoption.

Cost: While advanced memory technologies like HBM and persistent memory offer performance benefits, they often come with higher costs. Balancing cost and performance will be important for widespread adoption, especially among budget-conscious organizations.

Reliability and Longevity: New memory technologies must be reliable and capable of withstanding continuous operation, ensuring stability in enterprise environments.

Security: As memory technology evolves, so do security concerns. Protecting sensitive data stored in memory from vulnerabilities will be essential, with encryption and error-correction technologies playing critical roles.

Conclusion

The future of server RAM is marked by significant advancements, such as DDR5, 3D stacking, HBM, NVMe, and persistent memory. These innovations will enable faster, more efficient, and reliable memory solutions for data centers and enterprises. As AI, edge computing, and data center optimization drive increasing demands, server RAM's role in modern computing environments will continue to grow. However, compatibility, cost, reliability, and security challenges must be addressed for these technologies to reach their full potential, promising a more powerful and efficient computing future.

Want to Buy Server RAM in Bulk at an Affordable Price from VSTL?

If you're looking to buy server RAM in bulk at an affordable price, consider options from a reliable supplier that offers high-quality, cost-effective memory solutions. Purchasing in bulk can help reduce overall costs while ensuring that your business or data center has the necessary resources to support growing demands. Whether you need DDR4, DDR5, or other advanced memory technologies, choosing a trusted provider ensures that you receive top-tier performance, reliability, and efficiency for your server infrastructure.

Future of Server RAM: Cutting-Edge Technologies and Key Trends

Explore the future of server RAM with insights on emerging technologies and trends, including DDR5, 3D stacking, HBM, NVMe in this blog.

#VSTL #Bulk #RAM #wholesaler #supplier

0 notes

maychusieutoc1 · 1 year ago

Text

Giới thiệu về Xeon Platinum 8280

Xeon Platinum 8280 là một trong những dòng vi xử lý hàng đầu của Intel, được thiết kế đặc biệt để đáp ứng nhu cầu tính toán cao cấp và công việc đòi hỏi sức mạnh tính toán lớn. Với hiệu suất vượt trội và khả năng đa nhiệm mạnh mẽ, sản phẩm này là lựa chọn lý tưởng cho các ứng dụng doanh nghiệp, máy chủ, và trung tâm dữ liệu.

Đặc điểm kỹ thuật chính:

Hiệu suất đỉnh cao: Xeon Platinum 8280 sử dụng công nghệ xử lý tiên tiến nhất của Intel, cung cấp hiệu suất đỉnh cao với tần số xung nhịp cơ bản lên đến 2.7 GHz và có thể tăng tối đa lên đến 4.0 GHz với Intel Turbo Boost Technology.

Khả năng xử lý đa nhiệm: Với khả năng xử lý đa nhiệm ổn định, Xeon Platinum 8280 cho phép chạy đồng thời nhiều ứng dụng và công việc đa dạng mà không giảm đi hiệu suất.

Hỗ trợ bộ nhớ DDR4: Sản phẩm này hỗ trợ bộ nhớ DDR4 với công nghệ Intel Optane DC Persistent Memory, giúp tăng cường khả năng lưu trữ và xử lý dữ liệu một cách hiệu quả.

Bảo mật cao cấp: Với các tính năng bảo mật tích hợp sâu vào phần cứng và phần mềm, Xeon Platinum 8280 đảm bảo an toàn cho dữ liệu và ứng dụng, từng bước đi của bạn trên mạng.

Hỗ trợ công nghệ tiên tiến: Sản phẩm này hỗ trợ các công nghệ tiên tiến như Virtualization, Intel AES New Instructions (Intel AES-NI), và Intel Advanced Vector Extensions 512 (Intel AVX-512), giúp tối ưu hóa hiệu suất và khả năng xử lý.

Ứng dụng:

Xeon Platinum 8280 được thiết kế để sử dụng trong các môi trường doanh nghiệp, máy chủ và trung tâm dữ liệu, bao gồm:

Tính toán đám mây (Cloud Computing): Cho phép triển khai và quản lý các ứng dụng đám mây phức tạp và đòi hỏi nhiều tài nguyên tính toán.

Phân tích dữ liệu lớn (Big Data Analytics): Xử lý lượng dữ liệu lớn, phức tạp để tạo ra thông tin chiến lược và quyết định kinh doanh.

Mô phỏng và mô phỏng thử nghiệm (Simulation and Testing): Dùng để thử nghiệm và mô phỏng các mô hình phức tạp, từ kỹ thuật số đến sinh học và kỹ thuật.

Học máy và Trí tuệ nhân tạo (Machine Learning and Artificial Intelligence): Hỗ trợ trong việc huấn luyện mô hình và xử lý các tác vụ tính toán phức tạp của học máy và trí tuệ nhân tạo.

Với hiệu suất mạnh mẽ và tính linh hoạt cao, Xeon Platinum 8280 là một sự lựa chọn hàng đầu cho các ứng dụng yêu cầu sức mạnh tính toán lớn và đáng tin cậy.

Xem thêm: https://maychusieutoc.vn/intel-xeon-platinum-8280/

0 notes

infomen · 10 days ago

Text

Liquid‑Cooled 2U High‑Density Server – HexaData HD‑H263‑S62 VerGen002

The HexaData HD‑H263‑S62 Ver Gen002 is a cutting‑edge liquid‑cooled, 2U, 4‑node rear‑access server powered by 4th Gen Intel® Xeon® Scalable Processors and Intel® Xeon Max Series CPUs. It supports DDR5 memory (up to 16 DIMMs per CPU), Intel® Optane™ Persistent Memory 300 Series, PCIe Gen5 and OCP 3.0 slots, dual 3000 W Titanium‑rated redundant PSUs, and advanced AI acceleration suitable for HPC, deep learning, and bandwidth‑intensive workloads. For more details, Visit: Hexadata HD-H263-S62 Ver: Gen002 | 2U High Density Server Page.

#liquid cooled server #2U high density #Intel Xeon Max #DDR5 memory #Optane Persistent Memory 300 #PCIe Gen5 #OCP 3.0 #HPC server

0 notes

govindhtech · 2 years ago

Text

Intel Xeon Cascade Lake CPU Features

The 2nd Generation Xeon Scalable (Cascade Lake) brand of processors will no longer be manufactured by Intel. This news comes after the company made the announcement. It is incredible that Cascade Lake has been around for as long as it has, given that it is two generations behind the CPUs that Intel is now producing (4th Generation Xeon Scalable Sapphire Rapids), yet it has. When this is taken into consideration, it is not hard to understand why the former has been around for such a long time.

Features of the Intel Xeon Cascade Lake CPU

Cascade Lake has been around since 2019, which is the year that it was released by Intel to replace the Skylake microarchitecture, which had been around for a very long period. Cascade Lake is intended to be an improvement over Skylake in a number of ways. You poor thing, Cascade Lake, have gone through a lot of trouble in your life.

Due to the unrelenting competition presented by AMD’s 7nm EPYC Rome CPUs, Intel was forced to make a hasty decision to discontinue several of the Cascade Lake Xeon SKUs that it had previously released. At the same time, it was necessary for the corporation to lower the pricing of the products that were still available. Cascade Lake underwent a refresh not long after that, and not long after that, Xeon Cascade Lake Refresh components were released with a price reduction of up to sixty percent for each core.

Those of you who are familiar with Intel are surely aware that the manufacturer of chips does not make it a practice to cut the costs of its CPUs, much less to issue an update in such a short amount of time. Those of you who are not familiar with Intel may not be aware that Intel has released an update to its processors in such a short period of time.

Cascade Lake’s widely fragmented feature set was a contributor to the collapse of the microarchitecture, which was caused by a combination of factors. One example is that not all Cascade Lake chips were able to support the same amount of memory or Optane DC Persistent Memory DIMMs. On the other hand, AMD’s EPYC Rome product line offered consumers a consistent experience across all of the company’s several product iterations by providing the same feature set.

The manufacturing of Intel’s Cascade Lake-X (high-end desktop) and Cascade Lake-W (workstation) processors was halted in July of this year. The Xeon chips are the next component that will be removed from the system, as was to be expected given the circumstances. Both the tray and packaged forms of the Cascade Lake Xeon CPU will be discontinued as a result of the decision to halt production of the device. PCN is an abbreviation for “Product Change Notification,” and the document that Intel provided featured a list of 68 different Cascade Lake models.

Customers of the semiconductor company have until April 2024 to finalize their purchases with a local Intel representative if they want to do so. Cascade Lake won’t be completely taken off the market for at least another few of years, as Intel has guaranteed that it will fulfill all outstanding orders for Cascade Lake Xeon by October 2026. This date is the latest that Cascade Lake will be completely removed off the market.

Intel stressed in a related PCN report that the company’s attitude toward embedded customers has not changed and that there has been no modification to that policy. Therefore, the 22 people who are still alive today who are considered to be part of the Cascade Lake bloodline are those who have Cascade Lake in their processors.

It should not come as a surprise that the Cascade Lake embedded SKUs will be around for a little bit longer than their socket counterparts because embedded products have a longer life cycle than their socket equivalents. This is because embedded products have a longer life cycle than their socket equivalents. Finally, the transition of Intel’s Cascade Lake embedded chips to the Intel Embedded Architecture has been finished. This change, which will take effect after October 2026 and ensure continued support, will take place.

#govindhtech #technology #technews #news #cpu #intel #cascadelake #amdepyc #amd

0 notes

timestechnow · 5 years ago

Link

#mouser electronics #intel #optane persistent memory

0 notes

semiindustry · 5 months ago

Text

Next-Generation Memory Market: Trends, Growth Projections, and Key Players

The demand for faster, more efficient, and higher-capacity memory solutions is rising as industries increasingly rely on advanced computing technologies. Traditional memory technologies like DRAM and NAND flash are reaching their physical and performance limits, paving the way for next-generation memory (NGM) solutions. This new wave of memory technology, including MRAM, ReRAM, 3D XPoint, and NRAM, is designed to offer improved speed, energy efficiency, and durability. As artificial intelligence (AI), the Internet of Things (IoT), and 5G networks expand, next-generation memory is becoming an essential component for data storage and processing.

Download PDF Brochure @ https://www.marketsandmarkets.com/pdfdownloadNew.asp?id=632

Market Trends Driving Growth

1. Shift Toward High-Speed and Low-Power Memory

With the proliferation of AI, machine learning, and big data analytics, computing workloads require memory solutions that offer higher bandwidth and lower latency. Next-generation memory technologies like MRAM (Magnetoresistive RAM) and ReRAM (Resistive RAM) provide significantly faster read/write speeds compared to conventional DRAM and NAND flash, making them ideal for AI applications and edge computing.

2. Increasing Demand from Data Centers

Cloud computing and data-intensive applications are fueling the demand for high-performance storage solutions. Next-generation memory offers advantages such as non-volatility, which ensures data retention even during power failures. Technologies like 3D XPoint, developed by Intel and Micron, bridge the gap between DRAM and NAND flash by providing persistent memory with high endurance and speed.

3. Integration with IoT and Edge Devices

The rapid adoption of IoT devices has created a need for memory solutions that consume less power while maintaining high-speed performance. Resistive RAM (ReRAM) and Ferroelectric RAM (FeRAM) are being integrated into IoT devices to provide reliable, low-power, and real-time data processing capabilities.

4. Rising Adoption in Automotive and Industrial Sectors

The automotive industry, particularly in autonomous vehicles, requires memory solutions that can handle real-time data processing with high reliability. MRAM and Spin-Transfer Torque MRAM (STT-MRAM) are gaining traction as they provide faster write speeds and higher durability, which are crucial for automotive applications.

Growth Projections

The next-generation memory market size was valued at USD 6.2 billion in 2023 and is estimated to reach USD 17.7 billion by 2028, growing at a CAGR of 23.2% between 2023 to 2028. Several factors are contributing to this rapid expansion:

Increased investments by leading semiconductor companies in advanced memory solutions.

Growing demand for AI-based applications requiring high-speed memory.

Expansion of 5G networks, which enhances the need for faster and more energy-efficient storage solutions.

Technological advancements improving the scalability and cost-effectiveness of next-generation memory.

Key Players in the Next-Generation Memory Market

Several major companies are leading the development and commercialization of next-generation memory technologies. Some of the key players include:

1. Intel Corporation

Intel has been at the forefront of next-generation memory with Optane memory (3D XPoint technology), designed to bridge the performance gap between DRAM and NAND storage.

2. Micron Technology, Inc.

Micron, a leading name in the semiconductor industry, has played a vital role in advancing 3D NAND and 3D XPoint technology. The company continues to explore innovative non-volatile memory solutions.

3. Samsung Electronics

Samsung is actively developing MRAM, ReRAM, and FeRAM for various applications, including smartphones, data centers, and AI-based workloads.

4. Western Digital Corporation

Western Digital focuses on next-generation storage solutions tailored for high-performance computing, automotive applications, and enterprise data centers.

5. SK Hynix

SK Hynix is investing heavily in emerging memory solutions and has made significant progress in developing MRAM and other advanced memory technologies.

Challenges and Future Outlook

Despite the promising growth, the next-generation memory market faces challenges such as high development costs, integration complexity, and competition from traditional memory technologies. However, with continuous R&D efforts and increasing adoption across industries, next-generation memory is expected to become a mainstream solution in the coming years.

As AI, IoT, 5G, and edge computing continue to evolve, next-generation memory will play a crucial role in shaping the future of data storage and processing. Companies investing in innovative memory technologies will gain a competitive edge, driving the market toward exponential growth.

#next generation #technology

0 notes