10 use cases of Nvidia A100 with Arkane Cloud

10 use cases of Nvidia A100 with Arkane Cloud

10 use cases of Nvidia 100 with Arkane Cloud

1. Accelerating Deep Learning and AI Training

The Nvidia A100, integrated with Arkane Cloud, offers unprecedented acceleration for machine learning and AI training tasks. This combination provides an unrivaled platform that drives computational performance to new heights.

Users can take advantage of the A100’s third-generation Tensor Cores, delivering up to 4x the AI performance of the previous generation : Nvidia V100. This power, coupled with Arkane Cloud’s seamless deployment and scalable infrastructure, ensures your AI projects are not just feasible but incredibly efficient.

Leverage the Nvidia A100 with Arkane Cloud today and propel your AI and deep learning tasks into the future.

2. Unleashing Computational Power: Nvidia A100 in Scientific Simulations

Beyond the realm of AI and machine learning, the Nvidia A100 also shines in scientific simulations. Its remarkable computational power and high-bandwidth memory make it the ultimate engine for running complex simulations.

Researchers and scientists can run larger, more accurate simulations faster than ever before, achieving insights and breakthroughs in less time. The A100’s enhanced multi-instance GPU (MIG) capability allows for resource partitioning, enabling users to run multiple smaller simulations concurrently without sacrificing performance.

When integrated with the Arkane Cloud, scientists gain the flexibility and scalability to run their simulations with ease, no matter the scale. Adopt this server with Arkane Cloud for your scientific simulations and revolutionize your research.

3. Transforming Medical Imaging: Applications in Healthcare

In the healthcare sector, the Nvidia A100 can significantly transform medical imaging. The robust GPU technology coupled with high-speed data processing capabilities enhances diagnostic accuracy and reduces processing time. Radiologists can hence analyze complex medical images with unprecedented precision and detail.

The A100’s ability to handle enormous datasets also offers significant advantages in the field of genomics, enabling researchers to conduct comprehensive genetic analyses and make breakthrough discoveries more rapidly.

When used in conjunction with Arkane Cloud’s scalable infrastructure, healthcare professionals and researchers can unlock new possibilities in diagnosing, treating, and potentially curing diseases. Embrace the Nvidia A100 and Arkane Cloud in the healthcare field and take a significant leap towards advanced medical solutions.

4. Financial Insights Amplified: Nvidia A100 in Quantitative Analysis

In the competitive world of finance, the Nvidia A100 shines as a powerful tool for quantitative analysis. Its unrivaled processing speed and capacity for handling vast datasets make it an invaluable asset for financial analysts and investors.

By rapidly sifting through and interpreting complex financial data, the A100 can provide insights that drive investment strategies and ultimately, financial success. Furthermore, the compatibility of the A100 with Arkane Cloud’s scalable infrastructure optimizes computation time and efficiency, allowing for real-time analysis of market trends and fluctuations.

With the Nvidia A100 and Arkane Cloud, embrace a new era of financial analytics where data-driven insights become readily accessible.

5. Revolutionizing Energy Exploration: Nvidia A100 in Oil and Gas

In the field of oil and gas, the Nvidia A100 ushers in a new era of efficiency and precision. The graphical processing power of the A100 enables the rapid processing of seismic data, facilitating the identification of potential drilling sites with unprecedented accuracy.

This reduces operational costs, increases yield, and minimizes environmental impact. In addition, the A100’s capability to integrate with Arkane Cloud’s scalable infrastructure provides oil and gas companies with the ability to manage and analyze vast amounts of data in real time.

This results in more informed decision-making and strategic planning. With Nvidia A100 and Arkane Cloud, discover a smarter, greener, and more profitable future in energy exploration.

6. Fast-Tracking Drug Discovery: Impact on Pharma Research

In the pharmaceutical sector, the Nvidia A100 is set to revolutionize drug discovery and development. Its high computational ability enables the simulation of complex biological systems and the rapid analysis of genetic data, accelerating the process of drug discovery.

This not only hastens the time to market for new drugs, but also reduces R&D costs significantly. Additionally, the integration of A100 with Arkane Cloud’s scalable infrastructure facilitates real-time drug modeling and prediction, empowering researchers with deeper insights and fostering the development of more effective, personalized therapies.

Adopt the Nvidia A100 and Arkane Cloud, and fast-track the journey from lab to patient, creating a healthier future for all.

7. Predicting Climate Futures: Nvidia A100 in Climate Modeling

In the realm of environmental science, the Nvidia A100 is a game-changer for climate modeling. Its powerful computational capacity enables the processing of vast amounts of climate data, allowing for the creation of highly detailed and accurate climate models.

With these models, scientists can predict future climate trends and potential environmental crises with greater precision than ever before.

Moreover, the seamless integration of A100 with Arkane Cloud’s scalable infrastructure enables real-time analysis and modeling of climate data, providing immediate and critical insights into our changing environment.

With the Nvidia A100 and Arkane Cloud, we can better understand, plan for, and mitigate the impacts of climate change, paving the way for a more sustainable future.

8. AI in Healthcare Revolution: Nvidia A100 Enhancing Diagnostics

The influence of the Nvidia A100 extends beyond research labs and environmental science, making significant strides in the field of healthcare diagnostics. The unprecedented computational prowess of A100, coupled with Arkane Cloud’s scalable infrastructure, powers sophisticated AI algorithms that drastically improve diagnostic accuracy.

For instance, AI models trained on large-scale medical datasets can detect subtle patterns and anomalies in diagnostic images that may be overlooked by the human eye, enabling early detection of diseases such as cancer.

Additionally, the A100 enables real-time processing and analysis of patient data, aiding in the provision of personalized patient care and improving treatment outcomes. Thus, by embracing the Nvidia A100 and Arkane Cloud, we can revolutionize healthcare diagnostics, enhancing the accuracy, speed, and efficiency with which we diagnose and treat illnesses.

9. NLP Advancements with Nvidia A100: Language Understanding Redefined

In the field of Natural Language Processing (NLP), the Nvidia A100 is pushing the boundaries, redefining what machines can understand and how they interact with human language. Its exceptional computational abilities enable complex language models that can comprehend and generate human-like text, paving the way for more nuanced and effective AI communication.

When paired with Arkane Cloud’s robust infrastructure, developers can train these intricate models faster and more efficiently, accelerating the advancement in AI language capabilities. This GPU is not just transforming language understanding, but also creating more intelligent, responsive, and human-like AI interfaces.

In this era of digital communication, the combination of this card and Arkane Cloud is driving AI towards a future where they can seamlessly engage in human conversations, understand context, and provide relevant responses.

10. Real-Time Graphics Rendering : Visualizing the Future

The Nvidia A100 is redefining the way we visualize data and graphics, making real-time rendering a reality. Its superior processing power supports high-resolution graphics and complex visual effects, enabling designers and artists to create stunning visual experiences.

This opens up new avenues for industries such as film and animation, architecture, and product design, where realistic visualizations can enhance the quality of work and customer experiences.

When combined with Arkane Cloud’s infrastructure, the A100 allows for faster rendering times, enabling real-time collaboration and faster project turnarounds. With Nvidia A100 and Arkane Cloud, we’re empowering creators to visualize the future, today.

Deploying Nvidia A100 solution with Arkane Cloud

Choosing to deploy the Nvidia A100 with Arkane Cloud is like investing in the future. Together, these platforms bring incredible opportunities for businesses and individuals to fully tap into the power of AI and deep learning for problem-solving.

With Arkane Cloud’s robust infrastructure and the A100’s mighty processing capabilities, heavy computational tasks become a breeze, leading to faster and more accurate data analysis. This means businesses can tackle issues in real-time, make data-driven decisions, and predict trends, giving them a competitive edge.

And hey, the A100’s amazing graphics rendering abilities allow creators and designers to craft mind-blowing visual experiences, revolutionizing industries that rely on visual content. So go ahead, embrace the Nvidia A100 and Arkane Cloud, and unlock a world of possibilities.

Register here to get access to our Nvidia A100 servers or contact us for a long term project.

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For what purpose do you require RTX A5000 ?

For what purpose do you require RTX A5000 ?

Which purpose for RTX A5000 ?

As an engineer, choosing the right GPU for your development needs can be challenging. You need a graphics card that is powerful enough to handle complex applications and multitasking, while still being reliable and efficient. The RTX A5000 is the latest graphics card from NVIDIA, designed to meet the needs of developers, data scientists, engineers, and other professionals with demanding computational requirements. In this post, we’ll take a deeper dive into the features and benefits of the RTX A5000, and why it’s the perfect choice for multiple fields.

Powerful Performance

The RTX A5000 is powered by NVIDIA’s Ampere architecture, which features second-generation RT cores for real-time ray tracing and third-generation Tensor Cores for AI-enabled workflows. This card delivers up to 8192 CUDA cores and can achieve up to 222.2 Tflops Tensor Core performance, providing exceptional processing power for data science, AI, and other high-performance computing tasks. It can handle the most demanding applications with ease, making it an ideal choice for developers who need optimal performance.

Access to RTX A5000 datasheet.

Efficient Multi-tasking

The RTX A5000 comes with 24GB of GDDR6 memory and 384-bit memory bandwidth, allowing you to work on multiple applications and tasks simultaneously without any lag or delay. Its efficient power consumption and cooling center alleviate the risk of overworking, ensuring seamless multitasking action. This feature is especially important for developers dealing with medium projects that require efficient multitasking capabilities.




8 fields where RTX A5000 can achieve great performance

RTX A5000

1. Optimized Design and Modeling Applications:

For professionals working in design and modeling, the RTX A5000 GPU offers a significant advantage. Its robust performance and high memory capacity enable complex simulations, detailed designs, and intricate 3D modeling tasks to be executed smoothly and efficiently.

The GPU’s AI-acceleration capabilities further enhance these processes, enabling quicker iteration and improved accuracy. Whether developing intricate architectural designs, sophisticated animation sequences, or complex scientific models, the RTX A5000 stands as a powerful tool, compatible with industry-leading software such as Autodesk, Adobe, and Dassault Systèmes.

Its comprehensive support for these applications ensures that developers and designers can optimize their workflows, driving creativity and innovation to new heights.

2. Virtualization and Cloud Computing

The RTX A5000 is not only a powerful tool for design and modeling, but it also significantly enhances virtualization and cloud computing capabilities.

By effectively splitting the resources of the GPU, virtualization enables multiple users or applications to utilize the power of the RTX A5000 concurrently. This leads to increased efficiency and productivity, especially in collaborative environments.

Furthermore, when paired with cloud computing, the A5000’s capabilities become accessible anytime, anywhere, allowing for flexible work arrangements and collaboration regardless of geographical location.

The GPU’s compatibility with major virtualization software and cloud platforms ensures seamless integration with existing infrastructure, making the transition smooth and hassle-free.

It’s a versatile computing solution that drives efficiency and productivity in the modern digital workspace.

3. Medical and Scientific Sector: Accelerating Imaging and Analysis Work

In the medical and scientific sectors, the RTX A5000 is revolutionizing imaging and analysis work. Its high computational power accelerates the processing of vast amounts of data, aiding in complex tasks such as genetic sequencing, drug discovery, and the development of personalized medical treatments.

In the field of medical imaging, the A5000’s 3D rendering capabilities greatly enhance the visualization of medical scans, providing healthcare professionals with a more detailed and comprehensive understanding of patient conditions.

Its compatibility with leading medical imaging software ensures seamless integration and functionality. Moreover, the GPU’s virtualization capabilities allow multiple researchers or clinicians to access and analyze data concurrently, promoting collaborative research and diagnosis.

It’s a catalyst for advancements in the medical and scientific sectors, fueling discoveries that save lives and improve health outcomes.

3. Medical and Scientific Sector: Accelerating Imaging and Analysis Work

In the medical and scientific sectors, the RTX A5000 is revolutionizing imaging and analysis work. Its high computational power accelerates the processing of vast amounts of data, aiding in complex tasks such as genetic sequencing, drug discovery, and the development of personalized medical treatments.

In the field of medical imaging, the A5000’s 3D rendering capabilities greatly enhance the visualization of medical scans, providing healthcare professionals with a more detailed and comprehensive understanding of patient conditions.

Its compatibility with leading medical imaging software ensures seamless integration and functionality. Moreover, the GPU’s virtualization capabilities allow multiple researchers or clinicians to access and analyze data concurrently, promoting collaborative research and diagnosis.

It’s a catalyst for advancements in the medical and scientific sectors, fueling discoveries that save lives and improve health outcomes.

4. Realistic Rendering and Simulation: The Role of RTX A5000 in the Entertainment Industry

In the entertainment sector, the RTX A5000 is revolutionizing the landscape of realistic rendering and simulation. The GPU’s high-performance capabilities allow for the creation of stunning visual effects, lifelike animations, and immersive virtual reality experiences. It’s capable of rendering complex 3D models and environments with remarkable speed and precision, enabling artists and animators to bring their visions to life with greater fidelity and detail. For games and interactive media, the A5000 enhances real-time rendering, making for more dynamic, visually striking, and responsive experiences. Moreover, its compatibility with leading entertainment software ensures that creative professionals can seamlessly integrate the GPU into their workflows. The RTX A5000 is more than just a powerful GPU—it’s a game-changer in the entertainment industry, powering the next generation of digital creativity and enriching our media experiences.

5. Engineering and Architecture: Workflow Optimization in Design with RTX A5000

In the realm of engineering and architecture, the RTX A5000 is transforming the way professionals design and visualize their projects. The GPU’s high-performance capabilities facilitate the creation of detailed, accurate 3D models and simulations, enhancing precision and reducing the time spent on revisions. Real-time rendering enables architects and engineers to interact with their designs in new ways, visualizing changes instantaneously and making adjustments on the fly. This level of interactivity and realism dramatically improves project workflows, fostering greater efficiency and productivity. Moreover, the A5000’s compatibility with top industry software guarantees a seamless integration into existing workflows. The RTX A5000 does not merely offer a powerful GPU—it provides an invaluable tool for the engineering and architecture industry, streamlining design workflows and elevating the quality of output.

6. Artificial Intelligence: Fueling the Machine Learning Revolution with RTX A5000

In the rapidly evolving field of Artificial Intelligence, the RTX A5000 is proving to be a formidable ally. Machine Learning, a pivotal aspect of AI, relies heavily on the processing power and speed of GPUs like the A5000 for its complex computational tasks. The A5000’s robust architecture and high-performance capabilities result in faster data processing, thereby accelerating machine learning algorithms and reducing time-to-insight. These improvements are not merely incremental but transformative, enabling AI researchers and data scientists to build, train, and deploy AI models more efficiently. Additionally, the RTX A5000’s compatibility with leading AI software platforms ensures that it can be seamlessly integrated into machine learning workflows. Therefore, the RTX A5000 is not just a powerful GPU, but a catalyst in the AI revolution, accelerating machine learning processes and driving breakthroughs in AI research and application.

7. High-Performance Computing: The Role of RTX A5000 in Scientific Research

In the realm of scientific research, the RTX A5000 is quickly establishing itself as a game-changer. High-Performance Computing (HPC) involves crunching large volumes of data and performing complex computations at high speeds, tasks that the RTX A5000 is uniquely equipped to handle. Its high-performance capabilities and advanced features enable faster data processing and analysis, thereby expediting scientific research, and facilitating breakthroughs in fields as diverse as genomics, climatology, and astrophysics. By accelerating the simulation and modeling processes, the RTX A5000 allows researchers to tackle larger datasets, run more complex simulations, and obtain results faster than ever before. Additionally, with its seamless compatibility with leading HPC platforms, the RTX A5000 can be effortlessly incorporated into existing workflows. Therefore, the RTX A5000 is not merely a powerful GPU—it’s a key player in the scientific research landscape, revolutionizing the way research is conducted and paving the way for new discoveries.

8. Unleashed Creativity: Uses in Artistic Industries

In the artistic industries, the RTX A5000 is empowering creators to push the boundaries of their imaginations. The power and performance of this GPU make it ideal for tasks such as 3D modeling, rendering, and animation, enabling artists to create complex, photorealistic models with ease.

Its high memory capacity allows for the handling of large, intricate designs without compromising on performance, thereby ensuring smooth, efficient workflows. Furthermore, the RTX A5000’s hardware-accelerated ray tracing enables artists to simulate light and shadow with unprecedented accuracy, resulting in stunningly realistic visuals. Its compatibility with leading creative software means that it can be integrated seamlessly into existing workflows.

Thus, the RTX A5000 is not just a GPU—it is a tool that unlocks new creative possibilities, enabling artists to bring their visions to life in ways never before possible.


The RTX A5000 is the ideal GPU for developers, data scientists, engineers, and other professionals who require computational power, multitasking capabilities, and superior rendering performance.

Its advanced features in AI and machine learning, unparalleled rendering capabilities, compatibility with standard tools, and software applications make it a valuable asset to any team or individual looking for the best graphic processing unit money can rent.

As one of the most advanced graphics cards on the market, the decision to invest in the RTX A5000 ensures the ultimate computing power, while promoting maximum productivity for developers in all kinds of industries.

Get access to our RTX A5000 servers

The advantages of Nvidia H100 in Deep Learning

The advantages of Nvidia H100 in Deep Learning

The Unparalleled Power of NVIDIA H100 for Deep Learning

With the remarkable progress in machine learning, the use of GPUs has become essential for success in the field of artificial intelligence. NVIDIA, a pioneer in AI and high-performance computing, has recently unveiled the NVIDIA H100 GPU, sparking unprecedented excitement. This blog provides an overview of the performance and scalability of the NVIDIA H100 GPU, shedding light on the reasons and benefits of upgrading your ML infrastructure with this latest release from NVIDIA.

Nvidia H100

Unmatched Computing Performance

The NVIDIA H100 GPU is built on the NVIDIA Hopper architecture, offering several major performance improvements compared to its predecessor, the A100. With its fourth-generation Tensor Cores, the H100 doubles the computational throughput of each streaming multiprocessor (SM) compared to the A100, supporting data types like TF32, FP32, and FP64 for faster and more precise calculations.

In addition to an increased number of SMs, the H100 offers higher clock frequencies, operating at 1830 MHz for the SXM5 form factor and 1620 MHz for the PCIe version. These improvements result in significantly higher performance compared to the A100, providing a smoother and more responsive experience in the realm of machine learning.

The H100 also introduces a new FP8 data type, quadrupling the calculation rates of FP16 on the A100. Combined with the Transformer Engine of the NVIDIA Hopper architecture, the H100 can intelligently manage and dynamically choose between FP8 and 16-bit calculations, enhancing performance while maintaining high accuracy, particularly beneficial for transformer-based models.

Nvidia h100 ai record

Powering Scalability

The NVIDIA H100 GPU also offers impressive scalability to meet the growing demands of deep learning. Leveraging NVIDIA’s fourth-generation NVLink technology, the H100 ensures direct interconnectivity between GPUs, significantly increasing bandwidth and improving communication speed compared to PCIe lanes. With 18 NVLink interconnections, the H100 delivers a total bandwidth of 900 GB/s, a substantial improvement over the A100’s 600 GB/s.

The H100 also capitalizes on NVIDIA’s third-generation NVSwitch technology to facilitate fast communication between GPUs within a single node and between nodes. With this technology, the H100 offers an all-to-all communication bandwidth of 57.6 TB/s, ideal for large-scale distributed training and model parallelization.

Diverse Use Cases

The NVIDIA H100 Tensor Core GPU offers a diverse range of use cases for artificial intelligence and deep learning. Large models with high structured sparsity, such as language and vision models, experience up to 4x acceleration during training compared to the A100. The optimization of Tensor Cores for models with high structured sparsity makes the H100 ideal for large transformer-based models.

Large-scale data parallelization greatly benefits from the NVLink and NVSwitch technologies of the H100, offering a 4.5x increase in all-reduce throughput in configurations with 32 nodes and 256 GPUs. This improvement ensures efficient communication between GPUs, ideal for distributed training of complex models.

Lastly, model parallelization is a major use case for the H100, as many advanced models no longer fit on a single GPU, necessitating parallelization across multiple GPUs or GPU nodes. The NVSwitch system of the H100 enables exceptional performance in this context, as evidenced by the inference with the Megatron Turing NLG model, providing a 30x speedup compared to a reference A100 system with the same number of GPUs.

Nvidia h100 ML Performance


The NVIDIA H100 Tensor Core GPU offers unparalleled power for artificial intelligence and deep learning. With its superior performance featuring fourth-generation Tensor Cores, impressive scalability with NVLink and NVSwitch technologies, and advanced features like the Transformer Engine and FP8 data type, the H100 redefines the boundaries of high-performance computing. With its benefits for large language models, vision models, and various applications, the H100 is an essential asset for researchers and businesses seeking to push the boundaries of artificial intelligence.

The advantages of GPU cloud for startups

The advantages of GPU cloud for startups

What are the advantages of GPU cloud for startups and small businesses ?

In just a few short years, GPU technology has made significant leaps and transformed the realms of visual creation, data science, and scientific research. From integrated GPUs on PCs, we have entered the era of ultra-fast GPU server fleets on the Cloud: a true revolution for businesses and industries. But what about the advantages of GPU cloud for small businesses and future unicorns?

Des collaborateurs d’une startup profitant des avantages du GPU sur le cloud

Source : Photo de Israel Andrade sur Unsplash

When GPU Cloud disrupts creative professions and the world of data science

Looking back at dedicated and integrated GPU (Graphical Processing Unit) technology

The GPU (Graphical Processing Unit), which is literally translated as “graphical processing unit,” is more commonly known to the general public as a graphics processor. It is a computing unit traditionally dedicated to image processing and 2D, 3D, and video rendering. Working in conjunction with the CPU (Central Processing Unit), the GPU can sometimes be integrated into the same chip as the CPU, referred to as an integrated GPU. However, dedicated GPUs with their own processor can also be found, soldered onto graphics cards, in which case they are referred to as dedicated GPUs.

If central processors are directly equipped with a GPU, it means they have to share their memory, which limits the graphical computing power to relatively simple tasks. Examples include streaming video playback, basic image editing, office tasks, or less resource-intensive video games.

When the GPU is separated from the processor’s motherboard, it allows for a significant increase in computing power and faster access to images. Dedicated GPUs thus pave the way for highly efficient 3D rendering, the ability to create 360° visual effects, and video games with increasingly realistic graphics.

Functions and Uses of Dedicated GPUs in the Enterprise

The primary function of a GPU is to perform graphical rendering after processing the input information from the system. In parallel, it utilizes a buffer for data processing and storage. Distinguishing the GPU from the CPU isolates and unleashes the processing potential for images and data. This not only improves the visual experience but also reduces the overall strain on computer operation and achieves high-performance computations.

For professions such as architects, graphic designers, CAD engineers, videographers, and VFX artists, this significant technological advancement offers endless creative possibilities and prospects. To further leverage the computing power, both large and small companies now rely on GPU servers in the Cloud to train machine learning and deep learning algorithms.

The GPU technology is no longer limited to visual and graphic design professions. It now extends its power to a wide range of industries, including both large and small enterprises, as well as innovative startups harnessing the potential of AI.

A GPU server consists of one, but more commonly multiple GPU instances. Its purpose is to perform fast and reliable complex calculations for demanding graphical needs, as well as to develop new technologies or advance scientific research. You may be wondering why not simply use a regular server if high computational performance is desired. That’s because GPU servers are much more suitable. It’s essentially the same principle mentioned a few lines above. GPU technology detached from CPUs will be much faster on a dedicated server and capable of delivering much higher visual rendering quality. Speed and quality are highly sought-after advantages for any business dealing with a large volume of data and heavy IT and application requirements.

DilokaStudio pour Freepik

Hosted on the cloud, therefore centralized on an internet network, these fleets of servers and their data have the same functionalities as on a physical server but with significant advantages such as processing power and high storage capacity.

Companies no longer necessarily need to own and manage their physical hardware. They can rent cloud services from providers or third-party vendors who provision and configure the infrastructure and resources for them. And for certain organizations constrained by small physical spaces, limited budgets, but above all, high productivity requirements, cloud computing proves to be a significant asset.


Learn more about Arkane Cloud here

7 advantages of GPU Cloud for startups and small businesses

Flexibility, scalability, scalability

Hosting your GPU servers on the cloud provides small businesses with great flexibility. You can choose to significantly and quickly increase your resources without the need to invest in physical hardware. Depending on your needs, with just a few clicks, you can expand your resources and have access to more storage space. And if, on the other hand, the company experiences a decrease in activity or a quieter period, you can also scale back and reduce your resources.

Cost control and flexible pricing

Acquiring new licenses and hardware, especially during a sudden business growth, can be quite costly. The cloud eliminates the need for such expenses, and as mentioned in the previous point, it promotes on-demand consumption. Therefore, you only pay for what you consume. Some providers also offer monthly packages tailored to the specific needs and budget of the businesses.

Storage space, availability, and bandwidth

Pooling your resources, including GPU instances, in the cloud allows you to benefit from much larger storage spaces (at a lower cost) than if you were relying on on-premises hardware. Additionally, remote servers offer high-quality bandwidth and optimal data loading and availability times.

Speaking of data availability, hosting on the cloud provides access to data at any time and from a geographically diverse range. If your team works remotely or if your offices are in different time zones, this is a significant advantage not to be overlooked.

Infinite computing power and improved productivity

Another advantage of cloud computing in the era of everything-must-go-faster is the improvement of productivity and profitability. Training artificial intelligence models and performing complex calculations on physical hardware used to take a considerable amount of time, slowing down production and costing a fortune. With the introduction of GPUs in the market, things have significantly improved, and neural training could be up to 250 times faster*. Hosting GPUs on the Cloud has further accelerated these performances, freeing up time to focus on business and productivity.”

Note: *The accuracy of the translation may vary depending on the context and intended meaning of “neuronal training could be up to 250 times faster.

*Source : Indigo

Maintained control over your resources while benefiting from deployment and maintenance support

Opting for dedicated server rentals on the Cloud allows you to maintain full control over your resources and have servers exclusively for your employees. This means you won’t be sharing resources like in shared server hosting. However, service providers will typically handle the deployment, management, and maintenance of the server fleets on the cloud. This saves significant time and provides peace of mind for businesses.

Enhanced security

Cybercrime has reached unprecedented levels in recent years, and one particular threat, DDoS attacks, gives headaches to IT directors. A Distributed Denial of Service (DDoS) attack floods your system with traffic or overwhelms it with information, causing your servers and networks to become unresponsive, rendering them inaccessible. It’s a grim prospect that cloud computing can counteract with a modern and reliable operating system.

Protection and backup of data in the event of disasters

Today, a large number of cloud providers offer highly efficient backup and disaster recovery plans in the event of on-site damages (such as floods, fires, etc.) or ransomware attacks that block access to locally stored data. Storing your valuable data in the cloud helps prevent costly and damaging losses. It seems that prevention is better than cure…

Definition, Differences, and Advantages of IaaS in Enterprises

Definition, Differences, and Advantages of IaaS in Enterprises

Infrastructure-as-a-Service (IaaS) in Enterprises: Definition, Differences, and Potential

In the cloud computing family, we have Infrastructure-as-a-Service (IaaS), the cloud model that closely resembles an on-premises infrastructure. Infrastructure-as-a-Service delegates the management, deployment, and security of the hardware aspect (without which nothing would be possible) of an enterprise to cloud service providers. So, what is IaaS? What are the differences compared to Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS) models, and most importantly, what are the advantages and use cases in the daily operations of a business?

Des collaborateurs d’une startup profitant des avantages du GPU sur le cloud

Source : DCStudio pour Freepik

IaaS, PaaS, SaaS: How to harness the power of cloud computing?

Enterprises: When cloud computing disrupts the way we consume IT.

A recent Gartner study estimates that by 2025, 51% of global IT spending by organizations will be dedicated to the cloud. In just two decades, cloud computing has disrupted the way businesses operate, from startups to multinational corporations, as well as how IT is consumed. But in the era of as-a-service and significant technological advancements, isn’t it the logical progression?

The principle of cloud computing is simple. It enables the delivery of remote IT services, such as:

  • Servers
  • Networking
  • Software solutions stacks
  • Databases
  • Application development tools
  • And many more

What explains this enthusiasm of businesses for the cloud? It’s because these services are now hosted in one or more data centers (in public, private, or hybrid mode) outside the organization’s premises. This means there is no longer a need to purchase hardware. Today, organizations prefer turning to on-demand services from cloud providers for the flexibility and convenience they offer: a pay-as-you-go payment system, ready-to-use hardware for application development, reliable service providers to rely on, and more.

Cloud computing encompasses various approaches, including Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), and Infrastructure-as-a-Service (IaaS). Since we specialize in GPU infrastructure deployment and management, this article will focus on IaaS.

Find out more about Arkane here 


Infrastructure-as-a-Service (IaaS): Definition and Principles

Everything is in the title (or almost). The principle of IaaS (Infrastructure-as-a-Service) consists of offering rental services for IT infrastructures from a cloud provider. And by infrastructure, we mean fleets of servers, integrated systems, or virtual machines.

The objectives of businesses are diverse. It could be to obtain greater computing power, storage, or backup capabilities, to connect networks, or to leverage a data center, for example, to work on artificial intelligence algorithms.

The rental of servers and virtualization services can also be highly useful for businesses involved in graphic content creation, video encoding, computer-aided design (CAD) software usage, or web development.

The advantages  of an Infrastructure-as-a-service

advantages of iaas

Renting infrastructures, especially virtual ones, saves businesses from all the inconveniences associated with purchasing physical equipment: the high costs, of course, but also the maintenance, which ultimately becomes very time-consuming for IT teams. Additionally, there is the question of hardware upgrades as a company evolves and technology needs change (which can happen rapidly). Releasing funds during those moments is not as simple as one might think. And a significant advantage is that the provider will be responsible for the security of the infrastructures.

With IaaS, it only takes a few clicks for businesses to provision or deprovision resources according to economic growth, peak activity periods, and quieter times. IaaS also encourages a consumption-based payment model, the famous pay-as-you-go: you only pay for what you consume and only for the time you have used those cloud services.


IaaS vs PaaS (Platform-as-a-service)

In an IaaS model, the third-party provider will deliver server, network, storage services, and also handle machine virtualization. With PaaS, the provider hosts the infrastructure in its own data centers, but also offers an on-demand platform and a stack of software solutions to enable the business to develop its own applications. Once again, businesses do not have to maintain the infrastructure and software related to application development and operation.

IaaS vs SaaS (Software-as-a-service)

In this third model of cloud computing, we completely move away from hardware considerations. With SaaS, the provider upon which the business relies will deliver one or more complete, ready-to-use applications accessible via a web browser. Everything surrounding these applications, including updates, patches, and operations, is managed by the provider. Finally, none of these SaaS applications are installed on the company’s infrastructure.

Uses and Potential of IaaS in Enterprises

Lift and shift migration or how to consolidate application assets in the workflow.

One of the major strengths of IaaS is its ability to facilitate the migration of applications and their data to the cloud without any modifications. This technique is known as lift and shift or rehosting, or even running as-is. The idea is to migrate an exact copy of an application, originally hosted on-premises, to a cloud environment while keeping the application’s architecture and code intact. For businesses, this method offers several uses and advantages.

  • It is a relatively fast process that does not require mobilizing an entire IT team. During the migration, the local application remains in place, and users can continue working on it without interruption and with the same level of quality.
  • Companies can now take advantage of a more powerful environment and hardware to run their applications or workloads without needing to invest in the physical infrastructure. It is now possible to provision various resources (network, storage, etc.) on-demand for optimal usage of this application portfolio.

  • In an era where data is considered the most valuable asset for companies, transferring data to the cloud is an excellent way to benefit from the security provisions offered by the cloud. Multi-factor authentication, cybersecurity experts, protection labels for sensitive data, and more, IaaS strengthens the security aspect for businesses through its advanced technologies

High-Performance Computing (HPC): Unleashing Tenfold Power for Science and Graphic Design Creation

Aggregation (or clustering) of servers and virtual machines in the cloud creates a kind of giant calculator that far exceeds the computing power of an on-premise PC or server. While a workstation with a 3 GHz processor can process 3 billion calculations per second, HPC can perform a few quadrillions. Yes, it’s quite impressive…

HPC consists of three main components: computing, networking, and storage. Programs and algorithms work simultaneously within the cluster, as if thousands of PCs were performing these tasks at the same time. The cluster is connected to the network, and the data storage component captures the results.

This real-time data processing capability leads to significant advancements in scientific research, data science, finance, and graphic design. And in very tangible ways, this is demonstrated through the discovery of vaccines, treatments for cancer and diabetes, immense progress in renewable energy, and films and games with spectacular visual effects, just to name a few.

Moreover, in the field of Data Science, it opens up opportunities to push machine learning and deep learning algorithms even further to combat banking fraud, develop autonomous vehicles, and more.

Enlightened data mapping and storage

Because it always comes back to data, Infrastructure-as-a-Service offers businesses the opportunity to structure, map, and, most importantly, better understand their data. There are several categories of enterprise data. In broad terms, there are strategic data that are used on a daily basis, sensitive data, and archives.

Having servers on-site as well as in the cloud allows for a more enlightened classification based on the needs and specificities of a company. For example, if you deal with healthcare data, it may be better to entrust their hosting to HDS-certified cloud providers. On the other hand, for your most strategic data that you use daily, it may be worthwhile to keep them on-site.

These different considerations lead to a certain level of reflection, which ultimately leads to a better understanding of one’s environment.

Définition, différences et avantages de l’IaaS en entreprise

Définition, différences et avantages de l’IaaS en entreprise

Infrastructure-as-a-service (IaaS) en entreprise : définition, différences et potentiel

Dans la famille du cloud computing, nous demandons l’IaaS, le modèle cloud qui se rapproche le plus d’une infrastructure sur site. L’Infrastructure-as-a service va ainsi confier à des prestataires cloud le soin de gérer, déployer et sécuriser le volet matériel (sans qui finalement rien ne serait possible) d’une entreprise. Alors qu’est-ce que l’IaaS ? Quelles différences avec les modèles PaaS et SaaS et surtout, quels en sont les avantages et les cas d’usage dans le quotidien d’une entreprise ?

Des collaborateurs d’une startup profitant des avantages du GPU sur le cloud

Source : DCStudio pour Freepik

IaaS, PaaS, SaaS : comment exploiter la puissance du cloud computing ?

Entreprises : quand le cloud computing bouleverse les façons de consommer l’informatique

Une récente étude Gartner estime que d’ici 2025, 51% des dépenses informatiques mondiales seront consacrées au cloud par les organisations professionnelles. En à peine deux décennies, le cloud computing a bouleversé les modes de travail des entreprises, de la startup à la multinationale, mais aussi les façons de consommer l’IT. Mais à l’ère du as-a-service et des grandes avancées technologiques, n’est-ce pas dans l’ordre logique des choses ?

Le principe du cloud computing est simple. Il permet de fournir des services informatiques à distance, comme : 

  • des serveurs
  • du réseau
  • des piles de solutions logicielles
  • des bases de données
  • des outils de développement d’applications
  • et bien d’autres encore

Comment expliquer cet engouement des entreprises pour le cloud ? Parce que désormais, on héberge ces services dans un ou plusieurs centres de données (en mode public, privé ou hybride) hors des murs de l’organisation. Cela signifie qu’il n’est plus forcément nécessaire d’acheter du matériel. Aujourd’hui, on préfère largement se tourner vers les services à la demande des fournisseurs cloud pour la flexibilité et le confort que cela offre : un système de paiement à la carte, du matériel prêt à l’emploi pour le développement des applications, des prestataires sur qui s’appuyer, etc.

Le cloud computing comporte plusieurs approches dont le SaaS (Software-as-a-Service), le PaaS (Platform-as-a-Service) et l’IaaS (Infrastructure-as-a-Service). Et puisque nous avons fait du déploiement et de la gestion d’infrastructures GPU notre cœur de métier, c’est sur l’IaaS que nous concentrerons cet article. 

Pour découvrir l’univers Arkane, c’est par ici 


Infrastructure-as-a-service (IaaS) : définition et principe

Tout est dans le titre (ou presque). Le principe de l’IaaS (Infrastructure-as-a-service) consiste à proposer des services de location d’infrastructures informatiques auprès d’un fournisseur cloud. Et par infrastructure, il faut comprendre des flottes de serveurs, des systèmes intégrés ou encore des machines virtuelles. 

Les objectifs des entreprises sont variés. Il peut s’agir d’obtenir une plus grande puissance de calcul, de stockage ou de sauvegarde, de mettre des réseaux en relation ou de tirer un parti d’un centre de données pour par exemple travailler des algorithmes d’intelligence artificielle

La location de serveurs et des prestations de virtualisations peuvent aussi se révéler fort utiles pour les entreprises qui créent des contenus graphiques, encodent de la vidéo, utilisent des logiciels de CAO ou développent des sites web.

Les avantages de l’Infrastructure-as-a-service

La location d’infrastructures, qui plus est, virtuelles évite aux entreprises tous les inconvénients liés à l’achat de matériel physique : les coûts élevés bien sûr, mais aussi la maintenance qui, à terme, s’avère très chronophage pour les équipes IT. S’ajoute aussi la question du renouvellement matériel au fur et à mesure de l’évolution d’une entreprise et des besoins en technologie (ce qui peut aller extrêmement vite). Débloquer une trésorerie durant ces moments-là n’est pas aussi simple que l’on pourrait penser. Et avantage non négligeable, c’est le fournisseur qui sera chargé de la sécurité des infrastructures.

Avec l’IaaS, il suffit de quelques clics pour que les entreprises se provisionnent ou se (dé)provisionnent en ressources, au gré de la croissance économique, des pics d’activité et des périodes plus calmes. L’IaaS encourage également un type de paiement à la consommation, le fameux pay-as-you-go : on ne paye que ce que l’on consomme et seulement le temps où l’on aura utilisé ces services cloud. 


IaaS vs PaaS (Platform-as-a-service)

Dans un modèle IaaS, le tiers prestataire va fournir des services de serveurs, de réseau, de stockage et assure aussi la partie virtualisation des machines. Avec le PaaS, le prestataire héberge l’infrastructure dans ses propres datacenters, mais va aussi fournir une plateforme à la demande et une pile de solutions logicielles pour permettre à l’entreprise de développer ses propres applications. Là encore, les entreprises n’ont pas à entretenir les infrastructures et les logiciels liés au développement et l’exploitation d’applications.

IaaS vs SaaS (Software-as-a-service)

Dans ce troisième modèle de cloud computing, on s’éloigne définitivement des considérations matérielles. Avec le SaaS, le prestataire sur lequel l’entreprise s’appuie va fournir une ou plusieurs applications complètes, prêtes à l’emploi et accessibles via un navigateur web. Tout ce qui tourne autour de ces applications, à savoir, les mises à jour, les correctifs et l’exploitation est géré par le prestataire. Enfin, aucune de ces applications SaaS n’est installée sur l’infrastructure de l’entreprise.

 Usages et potentiel de l’IaaS en entreprise

La migration lift and shift ou comment consolider son capital applicatif dans le workflow

L’un des gros points forts de l’IaaS va être de permettre la migration d’applications et de leurs données vers le cloud, sans rien modifier. Cette technique s’appelle le lift and shift (littéralement, “on prend et on déplace”) ou réhébergement ou encore exploitation en l’état. L’idée consiste à migrer une copie conforme d’une application, initialement hébergée  on premise, vers un environnement cloud en gardant intacts l’architecture de l’application et son code. Pour les entreprises, il faut voir en cette méthode plusieurs usages et avantages.

  • C’est un processus qui est assez rapide à effectuer et qui ne nécessite pas de mobiliser toute une équipe IT. Durant le temps de la migration, l’application locale reste en place et les utilisateurs peuvent continuer à travailler dessus sans interruption et avec le même degré de qualité.
  • Les entreprises peuvent désormais profiter d’un environnement et d’un matériel plus performant pour exécuter leurs applications ou leurs charges de travail, sans avoir eu besoin d’investir dans ledit matériel. Et il est désormais possible d’approvisionner à la demande ce patrimoine applicatif en ressources diverses (réseau, stockage…) pour un usage optimal. 
  • À l’heure où la data s’envisage comme le bien le plus précieux des entreprises, transférer ses données vers le cloud est un excellent moyen de tirer parti des prestations de sécurité qu’offre le cloud. Authentification multifacteur, experts en cybersécurité, labels de protections de certaines données sensibles, etc. l’Iaas renforce le volet sécurité des entreprises grâce à ses technologies de pointe.

Calcul haute performance (HPC) : une puissance décuplée au service de la science et de la création graphique

L’agrégation (ou cluster) de serveurs et de machines virtuelles dans le cloud crée une espèce de calculateur géant qui dépasse de loin la puissance de calcul d’un PC ou serveur on premise. Là où un poste de travail doté d’un processeur de 3 GHz arrive à traiter 3 milliards de calculs à la seconde, le HPC en effectue quelques quadrillions. Oui, ça fait son petit effet… 

Le HPC se compose de 3 grands éléments : le calcul, le réseau et le stockage. Des programmes et des algorithmes vont travailler simultanément au sein du cluster, comme si plusieurs milliers de PC effectuaient ces tâches en même temps. Le cluster est mis sur le réseau et la partie stockage des données va capturer les résultats. 

Cette capacité de traitement de la donnée en temps réel permet de faire de grandes avancées dans les domaines de la recherche scientifique, dans la data science, dans la finance et dans la création graphique. Et de manière très concrète, cela s’illustre par la découverte de vaccins, de traitements contre le cancer, le diabète, des progrès immenses dans le domaine des énergies renouvelables, des films et des jeux aux effets visuels spectaculaires, pour ne citer qu’eux. 

Enfin, dans le domaine de la Data Science, c’est la perspective de pousser encore plus loin les algorithmes de machine et deep learning pour lutter contre la fraude bancaire, développer des véhicules autonomes, etc. 

Une cartographie et un stockage plus éclairé de la donnée

Parce qu’on en revient toujours à la data, l’Infrastructure-as-a-service offre aux entreprises l’opportunité de structurer, cartographier, mais surtout de mieux comprendre leurs données. Il existe plusieurs catégories de données entreprise. Dans les grandes lignes, on trouve celles stratégiques que l’on va exploiter quotidiennement, celles dites sensibles et les archives. 

Disposer de serveurs sur site, mais aussi sur le cloud va permettre d’opérer une classification plus éclairée en fonction des besoins et des spécificités d’une structure. Par exemple, si vous traitez des données de santé, mieux vaut peut-être confier leur hébergement à des fournisseurs cloud agréés HDS. En revanche, pour vos données les plus stratégiques, dont vous avez usage quotidiennement, cela vaut sans doute la peine de les garder sur site.

Ces différents questionnements poussent à une certaine réflexion qui, à terme,  amène à une meilleure compréhension de son environnement.