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globalinsightblog · 2 months ago

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🧱 Composable Infra Market = $12.4B by 2034. The future’s modular.

Composable-Disaggregated Infrastructure (CDI) Market is undergoing a significant transformation, driven by the evolving needs of modern enterprises for agile, cost-effective, and scalable IT systems. As organizations increasingly rely on data-driven operations, traditional IT architectures often fall short in meeting dynamic resource demands.

CDI addresses this challenge by disaggregating compute, storage, and networking resources and recomposing them through software-based solutions as needed. This market, valued at $5.3 billion in 2024, is projected to reach $12.4 billion by 2034, reflecting a compound annual growth rate (CAGR) of 8.9%. The growing demand for flexible infrastructure in data centers and cloud service environments is a major contributor to this robust expansion.

Click to Request a Sample of this Report for Additional Market Insights: https://www.globalinsightservices.com/request-sample/?id=GIS23429

Market Dynamics

Several core factors are influencing the growth trajectory of the CDI market. The primary driver is the shift towards digital transformation across industries, compelling organizations to seek infrastructure that can adapt rapidly to changing workloads. CDI solutions enable businesses to pool resources and allocate them efficiently, thereby reducing hardware redundancy and optimizing performance. In addition, the rise of cloud-native applications and hybrid IT environments has increased the appeal of composable infrastructure due to its modularity and agility.

However, challenges remain. The complexity of integrating CDI into existing legacy systems can hinder adoption, particularly for smaller organizations lacking technical expertise. Concerns around data security, system interoperability, and regulatory compliance also present obstacles. Despite these hurdles, innovations such as AI integration and automation are mitigating some of these issues, making CDI more accessible and effective.

Key Players Analysis

The CDI market is competitive and rapidly evolving, with major players investing heavily in R&D to maintain their edge. Companies such as Hewlett Packard Enterprise (HPE) and Dell Technologies are leading the charge, offering sophisticated modular platforms that support a wide array of enterprise applications. Their focus on interoperability and simplified management tools makes their solutions particularly attractive.

Emerging innovators like Liqid, DriveScale, Nebulon, and VAST Data are also making waves by introducing highly specialized products aimed at specific market niches. These companies are gaining traction with their focus on flexibility, performance, and cost efficiency. Strategic collaborations, acquisitions, and expansions are common as players look to diversify their portfolios and deepen market penetration.

Regional Analysis

Geographically, North America holds the lion’s share of the CDI market, buoyed by early adoption of advanced technologies and a robust ecosystem of tech giants and cloud providers. The United States, in particular, leads with strong investments in data centers and AI-driven infrastructure projects.

Europe follows, with countries like Germany and the UK actively investing in digital transformation initiatives. Strict data protection laws in the region also encourage adoption of CDI systems that offer robust compliance features.

Asia Pacific is emerging as a high-potential region, driven by rapid digitization in countries such as China, India, and Japan. Government initiatives supporting smart cities and data infrastructure are accelerating CDI deployment.

Meanwhile, Latin America, the Middle East, and Africa are gradually entering the CDI space, focusing on modernizing legacy systems and enhancing operational efficiencies in public and private sectors.

Recent News & Developments

The CDI landscape is seeing notable innovation, especially with the growing integration of AI, ML, and containerization technologies. These advancements enable real-time resource allocation and predictive analytics, significantly enhancing IT agility.

New pricing models are emerging, with deployment costs ranging between $10,000 and $100,000 depending on scale and complexity. This shift is making CDI solutions more attractive to mid-sized enterprises.

In recent strategic moves, companies have ramped up acquisitions and partnerships to enhance technological capabilities. There is a marked focus on interoperability, ease of integration, and automated management, all of which are becoming critical differentiators in the market.

Browse Full Report : https://www.globalinsightservices.com/reports/composable-disaggregated-infrastructure-market/

Scope of the Report

This report provides an in-depth analysis of the global CDI market, offering insights into historical trends, current market dynamics, and future growth prospects. It covers multiple segments including type, product, technology, deployment, and end-users. Special attention is given to regional market trends, emerging players, and competitive strategies.

Additionally, the report evaluates market drivers, challenges, and opportunities using comprehensive tools such as SWOT, PESTLE, and value-chain analysis. It also considers the impact of regulatory frameworks and technological advancements on market development. This study serves as a valuable resource for stakeholders aiming to navigate the evolving CDI landscape and capitalize on future growth opportunities.

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tbrc34 · 2 months ago

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computer8920 · 7 months ago

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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.

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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

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govindhtech · 11 months ago

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AMD Instinct MI210’s 2nd Gen AMD CDNA Architecture Uses AI

GigaIO

GigaIO & AMD: Facilitating increased computational effectiveness, scalability, and quicker AI workload deployments.

It always find it interesting to pick up knowledge from those that recognise the value of teamwork in invention. GigaIO CEO Alan Benjamin is one of those individuals. GigaIO is a workload-defined infrastructure provider for technical computing and artificial intelligence.

GigaIO SuperNODE

They made headlines last year when they configured 32 AMD Instinct MI210 accelerators to a single-node server known as the SuperNODE. Previously, in order to access 32 GPUs, four servers with eight GPUs each were needed, along with the additional costs and latency involved in connecting all of that additional hardware. Alan and myself had a recent conversation for the AMD EPYC TechTalk audio series, which you can listen to here. In the blog article below, They’ve shared a few highlights from the interview.

Higher-performance computing (HPC) is in greater demand because to the emergence of generative AI at a time when businesses are routinely gathering, storing, and analysing enormous volumes of data. Data centres are therefore under more pressure to implement new infrastructures that meet these rising demands for performance and storage.

However, setting up larger HPC systems is more complicated, takes longer, and can be more expensive. There’s a chance that connecting or integrating these systems will result in choke points that impede response times and solution utilisation.

A solution for scaling accelerator technology is offered by Carlsbad, California-based GigaIO, which does away with the increased expenses, power consumption, and latency associated with multi-CPU systems. GigaIO provides FabreX, the dynamic memory fabric that assembles rack-scale resources, in addition to SuperNode. Data centres can free up compute and storage resources using GigaIO and share them around a cluster by using a disaggregated composable infrastructure (DCI).

GigaIO has put a lot of effort into offering something that may be even more beneficial than superior performance, in addition to assisting businesses in getting the most out of their computer resources.

GigaIO Networks Inc

“Easy setup and administration of rapid systems may be more significant than performance “Alan said. “Many augmented-training and inferencing companies have approached us for an easy way to enhance their capabilities. But assure them that their ideas will function seamlessly. You can take use of more GPUs by simply dropping your current container onto a SuperNODE.”

In order to deliver on the “it just works” claim, GigaIO and AMD collaborated to design the TensorFlow and PyTorch libraries into the SuperNODE’s hardware and software stack. SuperNODE will function with applications that have not been modified.

“Those optimised containers that are optimised literally for servers that have four or eight GPUs, you can drop them onto a SuperNODE with 32 GPUs and they will just run,” Alan stated. “In most cases you will get either 4x or close to 4x, the performance advantage.”

The necessity for HPC in the scientific and engineering communities gave rise to GigaIO. These industries’ compute needs were initially driven by CPUs and were just now beginning to depend increasingly on GPUs. That started the race to connect bigger clusters of GPUs, which has resulted in an insatiable appetite for more GPUs.

Alan stated that there has been significant increase in the HPC business due to the use of AI and huge language models. However, GigaIO has recently witnessed growth in the augmentation space, where businesses are using AI to improve human performance.

GigaIO Networks

In order to accomplish this, businesses require foundational models in the first place, but they also want to “retrain and fine-tune” such models by adding their own data to them.

Alan looks back on his company’s accomplishment of breaking the 8-GPU server restriction, which many were doubtful could be accomplished. He believes GigaIO’s partnership with AMD proved to be a crucial component.

Alan used the example of Dr. Moritz Lehmann’s testing SuperNODE on a computational fluid dynamic program meant to replicate airflow over the Concord’s wings at landing speed last year to highlight his points. Lehmann created his model in 32 hours without changing a single line of code after gaining access to SuperNODE. Alan calculated that the task would have taken more than a year if he had relied on eight GPUs and conventional technology.

“A great example of AMD GPUs and CPUs working together “Alan said. This kind of cooperation has involved several iterations. [Both firms have] performed admirably in their efforts to recognise and address technological issues at the engineering level.”

AMD Instinct MI210 accelerator

The Exascale-Class Technologies for the Data Centre: AMD INSTINCT MI210 ACCELERATOR

With the AMD Instinct MI210 accelerator, AMD continues to lead the industry in accelerated computing for double precision (FP64) on PCIe form factors for workloads related to mainstream HPC and artificial intelligence.

The 2nd Gen AMD CDNA architecture of the AMD Instinct MI210, which is based on AMD Exascale-class technology, empowers scientists and researchers to address today’s most critical issues, such as vaccine research and climate change. By utilising the AMD ROCm software ecosystem in conjunction with MI210 accelerators, innovators can leverage the capabilities of AI and HPC data centre PCIe GPUs to expedite their scientific and discovery endeavours.

Specialised Accelerators for AI & HPC Tasks

With up to a 2.3x advantage over Nvidia Ampere A100 GPUs in FP64 performance, the AMD Instinct MI210 accelerator, powered by the 2nd Gen AMD CDNA architecture, delivers HPC performance leadership over current competitive PCIe data centre GPUs today, delivering exceptional performance for a broad range of HPC & AI applications.

With an impressive 181 teraflops peak theoretical FP16 and BF16 performance, the MI210 accelerator is designed to speed up deep learning training. It offers an extended range of mixed-precision capabilities based on the AMD Matrix Core Technology and gives users a strong platform to drive the convergence of AI and HPC.

New Ideas Bringing Performance Leadership

Through the unification of the CPU, GPU accelerator, and most significant processors in the data centre, AMD’s advances in architecture, packaging, and integration are pushing the boundaries of computing. Using AMD EPYC CPUs and AMD Instinct MI210 accelerators, AMD is delivering performance, efficiency, and overall system throughput for HPC and AI thanks to its cutting-edge double-precision Matrix Core capabilities and the 3rd Gen AMD Infinity Architecture.

2nd Gen AMD CDNA Architecture

The computing engine chosen for the first U.S. Exascale supercomputer is now available to commercial HPC & AI customers with the AMD Instinct MI210 accelerator. The 2nd Generation AMD CDNA architecture powers the MI210 accelerator, which offers exceptional performance for AI and HPC. With up to 22.6 TFLOPS peak FP64|FP32 performance, the MI210 PCIe GPU outperforms the Nvidia Ampere A100 GPU in double and single precision performance for HPC workloads.

This allows scientists and researchers worldwide to process HPC parallel codes more efficiently across several industries. For any mix of AI and machine learning tasks you need to implement, AMD’s Matrix Core technology offers a wide range of mixed precision operations that let you work with huge models and improve memory-bound operation performance.

With its optimised BF16, INT4, INT8, FP16, FP32, and FP32 Matrix capabilities, the MI210 can handle all of your AI system requirements with supercharged compute performance. For deep learning training, the AMD Instinct MI210 accelerator provides 181 teraflops of peak FP16 and bfloat16 floating-point performance, while also handling massive amounts of data with efficiency.

AMD Fabric Link Technology

AMD Instinct MI210 GPUs, with their AMD Infinity Fabric technology and PCIe Gen4 support, offer superior I/O capabilities in conventional off-the-shelf servers. Without the need of PCIe switches, the MI210 GPU provides 64 GB/s of CPU to GPU bandwidth in addition to 300 GB/s of Peer-to-Peer (P2P) bandwidth performance over three Infinity Fabric links.

The AMD Infinity Architecture provides up to 1.2 TB/s of total theoretical GPU capacity within a server design and allows platform designs with two and quad direct-connect GPU hives with high-speed P2P connectivity. By providing a quick and easy onramp for CPU codes to accelerated platforms, Infinity Fabric contributes to realising the potential of accelerated computing.

Extremely Quick HBM2e Memory

Up to 64GB of high-bandwidth HBM2e memory with ECC support can be found in AMD Instinct MI210 accelerators, which operate at 1.6 GHz. and provide an exceptionally high memory bandwidth of 1.6 TB/s to accommodate your biggest data collections and do rid of any snags when transferring data in and out of memory. Workload can be optimised when you combine this performance with the MI210’s cutting-edge Infinity Fabric I/O capabilities.

AMD Instinct MI210 Price

AMD Instinct MI210 GPU prices vary by retailer and area. It costs around $16,500 in Japan.. In the United States, Dell offers it for about $8,864.28, and CDW lists it for $9,849.99. These prices reflect its high-end specifications, including 64GB of HBM2e memory and a PCIe interface, designed for HPC and AI server applications.

Read more on Govindhtech.com

#GigaIO #amd #amdinstinct #amdinstinctmi210 #amdcdna #amdepyc #govindhtech #news #technews #technology #technologytrends #technologynews

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yelloblogs · 1 year ago

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market-insider · 2 years ago

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Data Center Virtualization: Optimizing IT Infrastructure for the Cloud

The global data center virtualization market size is anticipated to reach USD 23.14 billion by 2030, growing at a CAGR of 16.5% from 2023 to 2030, according to a new report by Grand View Research, Inc. The requirement for unified and centralized management of data centers and the mounting need to reduce operating costs for organizations and enhance business agility are key factors driving the market. Factors such as the rising demand to decrease data center complexity, increasing spending on data center technology, rising demand for enhanced network security, and adoption of optimization services will also contribute to the growth of the market.

Data Center Virtualization Market Report Highlights

The server type segment is estimated to occupy the largest share of the market in 2022. It is projected to continue its dominance over the forecast period. The growth of server virtualization can be attributed to major companies coming up with a server virtualization solution, enabling capabilities, thereby attracting more businesses

By component, the software segment occupied the largest revenue share of around 79% in 2022. Risen adoption of virtualization software such as network virtualization, storage virtualization, and server virtualization in data centers is contributing to the market’s growth

By service, the optimization services segment is projected to witness the highest CAGR of more than 18% from 2023 to 2030. The growth of the optimization services segment can be attributed to its benefits, which include better data mobility, increased profitability, and enhanced security and compliance

By organization size, the small and medium-sized enterprises (SMEs) segment is projected to witness the highest CAGR of approx. 17% from 2023 to 2030. Effective campaigns in the data center virtualization industry offering solutions specific to SMEs have also been boosting SMEs' adoption of data center virtualization

By end-use, the healthcare segment is projected to witness the highest CAGR of around 18% from 2023 to 2030. The growth of the healthcare segment can be attributed to the increasing demand for easy and secure data sharing, and access to high-quality health records, among others

For More Details or Sample Copy please visit link @: Data Center Virtualization Market Report

Additionally, the COVID-19 pandemic has expanded the penetration of digital transformation. Growing adoption of smart devices, IoT, digital transactions, rising automation scope in manufacturing industries via industry 4.0 technologies, and potential for huge data generation in sectors including education, healthcare, BFSI, IT & telecom, and media & entertainment will accelerate the development of data centers, thereby fueling the market for data center virtualization.

More number of businesses are incorporating DevOps and cloud-native technologies onto the businesses development process, which has resulted in the lines between the modern container-based platforms and traditional virtualization platforms to blur; of which a major part can be attributed to organizations opting for cloud-native technologies in support of legacy applications or ones which is not suited for containerization. Organizations operate on a tightrope because they need to negotiate both worlds without burdening IT operations. This has resulted in more IT teams turning to composable disaggregated infrastructure (CDI). CDI can also provide resources on demand to accommodate different workloads, including applications running in VMs, bare metal, and containers in VMs.

#datacentervirtualization #datacenter #cloudcomputing #ITinfrastructure #ITprofessional #ITstrategy #datacentertransformation #datacenterefficiency #datacentercostsavings #datacenteroptimization #datacentercloud #digitaltransformation

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nayan03 · 3 years ago

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robusthpc · 3 years ago

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You don’t know it yet, but your GPUs are mostly left untouched even with finely tuned models and servers, so you end up wasting space, energy, and well.. your power bills. GigaIO™ solves this problem with FabreX – the highest performance, lowest latency rack-scale network you can get.GigaIO™ provides Composable Disaggregated Infrastructure solutions, which comes in both hardware and software. Check full post to know more.

#parallel storage #All flash storage

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research-reports-blogs · 2 years ago

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The composable-disaggregated infrastructure market revenue would be US$ 2.8 billion in 2022. The whole market is predicted to reach US$ 40.8 billion by 2033, growing at a CAGR of 27.8% between now and then.

According to the analysis, the market would be worth US$ 2.2 billion by the end of 2021 and US$ 22.7 billion by 2031. According to FMI, rapid technological improvements in the data center business have offered opportunities for the implementation of composable/disaggregated infrastructure.

Composable disaggregated infrastructure has become critical in increasing usage and productivity, hence fueling market growth.

#Composable Disaggregated Infrastructure Market

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wiseguysss · 4 years ago

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ruptureline · 5 years ago

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Late Fascism in Brazil? Theoretical Reflections

The pithy phrase “the bull, bullet, and bible bloc” captures the centrality of agribusiness, the arms industry, and religious conservativism in securing Bolsonaro’s victory.

The most enthusiastic typical supporter of Bolsonaro was evangelical, male, with above-average educational attainment, a salary more than five times the minimum wage, and residency in the south of the country.

Intermediate tiers of the social structure gravitated to Bolsonaro in large numbers while capital cohered behind him as a last way out of crisis.

Dylan Riley

“For the issue is not to explain why, in the aftermath of a severe financial and economic crisis in the capitalist core, accompanied by a massive upward transfer of wealth by ruling centrists, blue and red, right-wing —and, in a few instances, left-wing— outsiders have come to power,” Riley insists, “but rather why these politicians have largely remained within the established framework. In short, the question is not why our contemporary politics resembles those of the 1930s, but why it does not.”

Perry Anderson

“Fascism was a reaction to the danger of social revolution in a time of economic dislocation or depression,” he stresses. “It commanded dedicated cadres, organised mass movements and possessed an articulated ideology.”

“Nothing remotely comparable either in terms of a danger to the established order from the left, or of a disciplined mass force on the right, exists in Brazil today … In 2018, the Communist party of old was long gone, combative trade-unions were a back number, the poor passive and dispersed, the PT was a mildly reforming party, for years on good terms with big business. Breathing fire, Bolsonaro could win an election. But there is scarcely any organizational infrastructure beneath him and no need for mass repression, since there is no mass opposition to crush.”

Atilio Borón

Attached to this baseline, Borón makes four narrower claims. First, fascism involved a political configuration of power in which the dominant bloc was hegemonized by the national bourgeoisie. This fascist political formula was a means of resolving a crisis of hegemony brought on by the mass insurrectional capacities of the subaltern classes and internal contradictions within the ruling bloc at the close of the First World War. Today, transnational and financial capital have replaced the national bourgeoisies, and in the absence of its chief protagonist, no fascist regime is possible.

Third, classical fascisms in European history were regimes rooted in mass organization and mobilization, with the middle classes constituting their key support base. (...) In contradistinction, Borón (2019) expects Bolsonaro to deepen the depoliticization of Brazilian social life through the acceleration of civil society’s disaggregation and atomization.

Armando Boito Jr.

Boito Jr. (2019a) begins with Borón, identifying a theoretical ambiguity of argument insofar as Borón oscillates in his characterization of fascism as first having to do mainly with the state form (a deviation from the ideal mode of bourgeois democracy) and then later mainly with types of power blocs (led by national bourgeoisies). For Boito, it is correct to start with fascism as a problem of the state form, whereas it sows confusion to think of it in terms of power blocs. Fascism in Boito’s view is a form of state in the same way that bourgeois democracies and military dictatorships are forms of state. In actual historical cases of bourgeois democracies and military dictatorships, the power blocs in question have been composed of highly varied classes and class fractions: that is, there are many possible power bloc configurations within the same form of state. Why would we exclude this possibility from our definition of fascism? Even if it were true that national bourgeoisies have disappeared from the scene, as Borón contends (highly dubious), would the state form of fascism be an impossibility as a result? Why should we not consider the potentiality of new fascist forms with distinct power blocs appropriate to the novel setting of internationalized and financialized capital?

From a global perspective which takes into account the non-European world, the causal force of the First World War in the rise of fascism ought at least to be relativized (Traverso 2019a, 170–1). In the Argentine context, for example, the fascist tradition was rooted not in the experience of World War One but rather in “internal colonialism” and wars of extermination against the indigenous population.

In imperialist countries, the power bloc of fascist states will not resemble those of dependent capitalist societies. At the level of theory, it is therefore reasonable to imagine an eventual fascist state in Brazil serving the interests of international capital, rather than those of the national bourgeoisie, as in the classical interwar European experience.

It is therefore important to register, theoretically, that it is possible for a fascist movement to arrive in government and not to implant a fascist dictatorship. In the Brazilian case, for Boito, what we see is a neo-fascist ideology, a neo-fascist movement, and a government in which neo-fascists are engaged in a struggle for hegemony with other factions internal to the regime. Yet, instead of a fascist regime, Brazil under Bolsonaro remains a deteriorated bourgeois democracy in crisis (Boito 2019c).

It was precisely the antisystemic threat of communism that led European ruling classes to facilitate the entry of fascists into state power, more often than not through legal elections. Today, then, the absence of a credible antisystemic Left allows a certain space for the development of the radical Right in many parts of the world, but it also tends to constrain the depth of allegiances those in the Far Right can win from the capitalist classes, who prefer, in the absence of systemic threats to capital’s rule, more predictable political representation in the state (13).

In Brazil today, according to Boito, neo-fascism is not a response to an insurrectional anticapitalist movement since there isn’t one.

Bolsonaro’s grip on the grassroots organizations of the anti-impeachment movements of 2015 may be slipping, however, as the first two of the movements mentioned above have become openly critical of aspects of the government and have refused to participate in recent pro-Bolsonaro demonstrations in late May of 2019. The contrast with Narendra Modi’s ruling Bharatiya Janata Party (BJP) in India is clear in this respect. As Achin Vanaik (2018) has explained, the BJP is an ideologically disciplined and cohesive party, with a cadre or base developed over decades and an organization of violent foot soldiers that can be easily mobilized.

In lieu of the “homologies and repetitions” toward which one is oriented to detecting in the frameworks of Riley and Anderson, Traverso instead urges us toward “analogies and differences” through his historical comparison of the contemporary Far Right and classical fascism, always attentive to “this tension between history and language.”

And is not the ideology of the culturally authoritarian current of the government coalition centered on the aim of a military revival, this time accompanied by a popular cultural counterrevolution? Might this be the form that neo-fascism would assume in its early stages in twenty-first-century Brazil were it to hegemonize the state?

While there is then a relative autonomy to militia power, there is also a symbiotic relationship between the militias and the state apparatuses controlled by the Far Right. This established dynamic is gaining momentum under Bolsonaro.

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govindhtech · 1 year ago

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Samsung Unveils CXL Memory Pooling Technology

CXL memory pooling

Samsung unveiled its state-of-the-art CXL DRAM memory pooling product, the CXL Memory Module – Box (CMM-B), to highlight the expanding momentum in the CXL ecosystem. The Samsung CMM-B has a capacity of up to two terabytes (TB) and can hold eight CMM-D devices with the E3.S form factor. AI, in-memory databases (IMDB), data analytics, and other applications requiring large memory capacities may benefit from the enormous memory capacity combined with high efficiency of as much as 60 gigabytes-per-second (GB/s) as well as a latency of 596 a nanosecond (ns).

Samsung also showcased the first Rack-Level memory solution for highly scalable and composable disaggregated infrastructure in collaboration with Supermicro, a pioneer in Plug and Play Rack-Scale IT solutions worldwide. Unlike typical designs, which lack the flexibility and efficiency required for current applications, this innovative solution makes use of Samsung’s CMM-B to enhance memory capacity and bandwidth, allowing data centres to manage demanding workloads. Applications like AI, IMDB, data analytics, and more that need high-capacity memory may benefit from the enhanced memory capacity and high-performance of up to 60GB/s bandwidth per server.

Samsung CXL memory expander Reiterating its leadership in high-performance and high-capacity solutions for AI applications, Samsung Electronics, a global leader in advanced semiconductor technology, announced the extension of its Compute Express Link (CXL) memory module portfolio and demonstrated its most recent HBM3E technology.

What is CXL memory? Unlike DDR5 or HBM2E, CXL memory, usually referred to as CXL-attached memory, isn’t precisely a particular kind of memory. Rather, the Compute Express Link (CXL) connection standard makes this idea possible.

CXL memory controller SangJoon Hwang, Corporate Executive Vice President, Head of DRAM Product and Technology at Samsung Electronics, and Jin-Hyeok Choi, Corporate Executive Vice President, Device Solutions Research America Memory at Samsung Electronics, utilised centre stage to announce the latest memory methods and talk regarding how Samsung Electronics is advancing HBM and Compute Express Link (CXL) in the AI era. The event was held in front of a full house at Santa Clara’s Computer History Museum. Gunnar Hellekson, vice president and general manager at Red Hat, and Paul Turner, vice president, product team, VCF division at VMware by Broadcom, joined Samsung on stage to talk about how their software solutions, when paired with Samsung’s hardware technology, are pushing the envelope in memory innovation.

According to Choi, “innovation in memory technology is essential for the advancement of AI.” As the leader in the memory market, Samsung is pleased to keep pushing innovation with products like the most sophisticated CMM-B technology in the business and potent memory solutions like HBM3E for demanding AI applications and high-performance computing. In order to jointly realise the full potential of the AI age, they are dedicated to working with their partners and providing for their clients.

CXL memory sharing The world’s first FPGA (Field Programmable Gate Arrays)-based tiered memory solution for hypervisors, known as the CXL Memory Module Hybrid for Tiered Memory (CMM-H TM), was also unveiled on stage by Samsung and VMware by Broadcom as part of project Peaberry. In order to address memory management issues, minimise downtime, optimise scheduling for tiered memory, and optimise performance all while drastically lowering total cost of ownership (TCO) this hybrid system combines DRAM and NAND storage in an Add-in Card (AIC) design factor.

Paul Turner said, “VMware by Broadcom is happy to collaborate with Samsung to bring new innovations in memory.” “A new innovation in CXL and a compelling value-proposition with significant TCO benefits, better utilization of expensive DRAM resources, and improved consolidation of server resources while delivering the same great performance are made possible by Samsung’s leadership in memory technologies and VMware‘s leadership in software memory tiering.”

CXL memory expansion CXL Memory Module Furthermore, Samsung demonstrated its CXL Memory Module DRAM (CMM-D) technology, which combines the CXL open standard interface with Samsung’s DRAM technology to provide effective, low-latency communication between the CPU and memory expansion devices. For the first time in the market, Red Hat, a pioneer in open source software solutions, successfully verified Samsung’s CMM-D devices with its business software last year. Through Samsung Memory Research (SMRC), the two businesses will keep working together to create CXL reference and open-source models in addition to working together on a variety of other storage and memory solutions.

Additionally, Samsung provided 2024 Memcon guests with a demo of its most recent HBM3E 12H chip, which is the first 12-stack HBM3E DRAM in the world and represents a breakthrough with the largest capacity in HBM technology. By using the company’s cutting-edge thermal compression non-conductive film (TC NCF) technology, the HBM3E 12H improves both product yield and vertical density of the chip by more than 20% when compared to its predecessor. Samsung intends to begin mass manufacturing of the HBM3E 12H during the first half of this year, and is presently providing samples to customers.

Enabling cxl memory expansion for in-memory database management systems In-memory database management systems (IMDBMS) might potentially circumvent the constraints of standard memory architectures by enabling CXL memory extension. Here’s how the idea is broken down:

Traditional Memory’s Drawbacks for IMDBMSs Capacity restrictions: The main memory (DRAM) of a server might easily get overloaded with large datasets utilised by IMDBMS. Performance is impacted as a result of forcing data switching to slower storage (SSD/HDD). Bottlenecks caused by latency: Accessing data from slower storage causes latency, which reduces the performance benefit of in-memory databases. Concerning Samsung Electronics Samsung’s revolutionary concepts and innovations inspire people all across the globe and help to build the future. Through its SmartThings ecosystem and open cooperation with partners, the firm is transforming the worlds of TVs, smartphones, wearables, tablets, home appliances, network systems, memory, system LSI, foundry, and LED solutions. It is also creating a seamless connected experience.