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AI-Optimized Hardware Solutions:

Accelerate AI Innovation with Cutting-Edge Hardware Solutions

Unlock the full potential of your artificial intelligence projects with our AI-Optimized Hardware Solutions. Designed specifically to meet the demands of intensive AI workflows, our cutting-edge hardware range accelerates AI model training and inference , ensuring your innovations move from concept to reality faster than ever. With a focus on speed, efficiency, and scalability, our solutions provide the necessary power to handle complex computations and large datasets, seamlessly integrating into your existing infrastructure. Whether you’re developing advanced neural networks, automating complex processes, or analyzing vast amounts of data, our hardware is engineered to boost performance and reliability. Embrace the future of AI with the tools that give you the competitive edge, driving your organization towards new heights of innovation and success.

Benefits of Specialized AI Hardware

As AI technologies continue to evolve, the need for specialized hardware that can handle the intensive demands of AI computations becomes crucial. AI hardware refers to the advanced array of processors, including GPUs, TPUs, and custom AI accelerators, specifically engineered to efficiently manage the massive data processing and complex matrix operations typical of AI tasks.

These components are not just faster than traditional CPUs; they are designed from the ground up to accelerate AI model training and inference, providing the backbone for breakthroughs in machine learning and deep learning.

By significantly reducing processing times, AI hardware enables researchers and developers to iterate on models more quickly and deploy AI solutions faster, bringing AI innovations from lab to market with unprecedented speed.

Understanding the capabilities and benefits of AI hardware is essential for any organization looking to leverage artificial intelligence to its fullest. With these tools, businesses can harness powerful computational resources to unlock new possibilities in data analysis, predictive modeling, and automated decision-making, propelling them into a new era of technological advancement.

Speed

Specialized AI hardware like GPUs and TPUs is designed for parallel processing, which divides complex tasks into smaller, simultaneous processes essential for AI model training. Unlike CPUs that handle tasks sequentially, GPUs process thousands of threads at once, significantly speeding up computations. This reduces the time for training and inference phases of AI models, accelerates experimentation, and facilitates quicker deployment of AI applications, especially in real-time data processing scenarios.

Energy Efficiency

Specialized AI hardware is designed to maximize performance per watt through architectural optimizations. These improvements allow for more computations with less power, lowering both operational costs and environmental impact. AI accelerators perform specific calculations more efficiently than general-purpose CPUs or GPUs, enhancing energy efficiency. This is crucial for organizations looking to expand AI capabilities while meeting stricter sustainability standards and reducing their carbon footprint.

Scalability

AI-specific hardware, with enhanced memory bandwidth and computational power, swiftly handles complex algorithms and large data sets, improving the reliability and accuracy of applications like natural language processing and computer vision. Its scalable infrastructure allows organizations to expand AI operations by adding more GPUs or AI accelerators as needed. This modular strategy ensures system efficiency and adaptability, facilitating the integration of new technologies without major reinvestment.

Reliability

Specialized AI hardware is designed for continuous, intensive computation, ensuring reliability for critical AI applications. These systems incorporate advanced cooling, error correction, and redundancy to handle operational stress and maintain continuous operation. This reliability is crucial in sectors like healthcare, autonomous driving, and financial services, where downtime poses financial and safety risks. Therefore, the dependability of AI hardware is essential for the effective deployment and sustainability of AI technologies.

Artificial Intelligence Dedicated Infrastructures based on NVIDIA GPU

NVIDIA Servers: Powering the Future of AI and Computing

NVIDIA’s server solutions leverage advanced GPU architectures, like the latest Ampere series, to deliver unparalleled processing power and efficiency. These servers are optimized for a variety of applications, including deep learning, scientific computation, and large-scale data analytics, providing the necessary tools to drive innovation and accelerate discovery in any organization. With NVIDIA’s commitment to continuous advancement in AI technology, their servers represent a cornerstone for enterprises aiming to

harness the power of artificial intelligence effectively and sustainably.

Dual AI Hardware Solutions: Powering Production and Fueling Innovation

We offer two specialized General AI hardware infrastructures tailored for distinct needs: our Production-Ready solution and our R&D-Focused option. The Production-Ready infrastructure is engineered for maximum reliability and compliance, ideal for critical environments where uptime is crucial, such as in healthcare and finance. It is robust but comes at a higher cost. Conversely, our R&D-Focused infrastructure is more budget-friendly, designed for experimental and developmental purposes where full production compliance isn’t a necessity. This setup is perfect for organizations looking to innovate and test AI models economically, allowing them to scale their operations to a Production-Ready environment when needed.

Powering Production

Designed for high-stakes environments, this infrastructure combines robust, high-performance configurations to ensure continuous, reliable operation. Ideal for critical sectors like healthcare and finance, it minimizes downtime risks despite its higher cost.

Fueling Innovation

This cost-effective R&D infrastructure supports innovation without the expense of full production compliance. It’s ideal for developing and testing AI models in pre-production phases, offering flexibility but not suited for all production requirements.

NVIDIA servers with L4 24GB Tensor Core GPU

Equipped with Nvidia L4 cards offering excellent value for money. Ideal for basic AI tasks and small model development, these cards ensure reliable and economical performance for standard machine learning and data analysis applications. Perfect for inference on models like LLaMA 3 7B or Mistral, they are ideal for small-scale deployments (These cards do not support MIG). This offering is mainly recommended for the inference of small models.

2 recommended configurations:

  • 2x L4 GPUs
  • 4x L4 GPUs.

Compatible with GPU Virtualization, very practical for small production or sandbox development.

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NVIDIA servers with L40s 48GB

Based on Nvidia L40s cards for superior performance and increased efficiency. Optimized for intensive AI workloads, L40s cards are perfect for the development and use of medium-sized models. Additionally, they offer better power management and improved performance. This offering can be used both for inference on models like LLaMA 3 70B, and for training and inference of smaller models like LLaMA 3 8B and Mistral.

3 recommended configurations:

  • 2x L40s GPUs
  • 4x L40s GPUs
  • 8x L40s GPUs (compatible mixtral 8x22b).

Compatible with GPU Virtualization, very practical for small production or sandbox development.

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NVIDIA servers with H100 80GB / H200 141 GB Tensor Core GPU

Powered by Nvidia H100/H200 cards for cutting-edge capabilities and maximum performance/power. Designed for the most demanding AI environments, these cards are recommended for the production and use of large-scale models. Ideal for training and inferring very large models such as Mixtral 7x8B or Mixtral 8x22B, they offer exceptional computing capabilities and groundbreaking acceleration, essential for advanced AI projects. Additionally, these cards support MIG (Multi-Instance GPU), allowing a single GPU to be partitioned into multiple smaller instances, thus providing flexibility and optimized resource utilization for varied and simultaneous workloads. This offering is highly recommended for production use in both the inference and training of large models like Mixtral or LLaMA 3 70B.

3 recommended configurations:

  • 1x H100 GPUs / 1x H200 GPUs
  • 2x H200 GPUs
  • 4x H100 GPUs / 4x H200 GPUs
  • 8x H100 GPUs / 8x H200 GPUs
  • H200 GPUs Cluster

Compatible with GPU Virtualization, very practical for small production or sandbox development.

Get View Our Offers with H100 and H200

Key Features of Our All Platform

Configurations

GPU(s)

Total GPU Memory

FP16 Performance

Recommended Usage

L4 2

2x NVIDIA L4 GPUs Tensor Core GPU

48 GB

484 TFLOPS

Machine Learning (dev) /
 Quantized LLMs

L4 4

4x NVIDIA L4 GPUs Tensor Core GPU

96 GB

968 TFLOPS

small LLM inference (ex. llama3 8B, mixtral 22)

L40s 2

2x NVIDIA L40s GPUs

96 GB

724 TFLOPS

medium LLM inference (ex. llama3 70B, mixtral 8x7B)

L40s 4

4x NVIDIA L40s GPUs

192 GB

1 448 TFLOPS

large LLM inference (ex. mixtral 8x22B)

L40s 8

8x NVIDIA L40s GPUs

384 GB

2 896 TFLOPS

Fine-tuning / medium LLM inference (ex. llama3 70B, mixtral 8x7B)

H100 1

1x NVIDIA H100 GPUs Tensor Core GPU

80 GB

1 513 TFLOPS

small LLM Fine-tuning / Inference

H100 2

2x NVIDIA H100 GPUs Tensor Core GPU

160 GB

3 026 TFLOPS

medium LLM Fine-tuning / Inference

H100 4

4x NVIDIA H100 GPUs Tensor Core GPU

320 GB

6 052 TFLOPS

large LLMs inference

H200 1

1x NVIDIA H200 GPUs Tensor Core GPU

141 GB

1 979 TFLOPS

medium LLM Fine-tuning / Inference

H200 2

2x NVIDIA H200 GPUs Tensor Core GPU

282 GB

3 958 TFLOPS

large LLMs inference / Fine-tuning

H200 4

4x NVIDIA H200 GPUs Tensor Core GPU

564 GB

7 916 TFLOPS

large LLMs inference / Fine-tuning

H200 8

8x NVIDIA H200 GPUs Tensor Core GPU

1 128 GB

15 832 TFLOPS

large LLMs Fine-tuning / Multi-large LLM inference

Dedicated Infrastructures Acquisition options

Three Ways to Acquire Equipment: Purchase, Lease, and Pay-per-Resource

We offers three flexible equipment acquisition methods: Purchase, Lease, and Pay-per-Use. Purchasing is ideal for long-term ownership, while leasing offers short-term use without upfront costs, allowing easy upgrades. Pay-per-Use suits occasional needs, tying costs directly to usage. This approach ensures clients efficiently access essential tools without financial strain.

Aquire

Ideal for long-term needs, purchasing equipment allows businesses to become the outright owners after the transaction is complete. This method is cost-effective over time, particularly for equipment that is essential and frequently used. It also eliminates any restrictions on usage that are common with other acquisition methods.

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Lease

This option provides the flexibility of using the latest equipment without the upfront costs associated with purchasing. Under a lease agreement, clients can use the equipment for a predetermined period while making regular payments. This is particularly advantageous for temporary projects or when upgrading equipment frequently. At the end of the lease term, the equipment is returned, offering the opportunity to renew, upgrade, or terminate based on current needs.

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Pay-per-Resource

Designed for companies that require specialized equipment but only on an occasional basis, this method ties the cost directly to the usage rate. It is an economically sensible choice when avoiding large capital expenditures and maintaining cash flow are priorities. Pay-per-Use ensures clients pay only for what they use, making it an ideal option for equipment that may not be needed continuously.

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Our Platforms for Gen AI Offers

Revolutionize Your AI
Capabilities with
Plug-and-Play Gen AI Platforms

We offer innovative Gen AI platforms that make AI infrastructure effortless and powerful. Harnessing NVIDIA’s H100 and H200 GPUs, our solutions deliver top-tier performance for your AI needs.
Our platforms adapt seamlessly, scaling from small projects to extensive AI applications, providing flexible and reliable hosting. From custom design to deployment and ongoing support, we ensure smooth operation every step of the way. In today’s fast-paced AI world, a robust infrastructure is key. At Iguana Solutions, we’re not just providing technology; we’re your partner in unlocking the full potential of your AI initiatives. Explore how our Gen AI platforms can empower your organization to excel in the rapidly evolving realm of artificial intelligence

Explore Our Platforms for Gen AI Offers

Tailored Solutions for Your Needs

Contact us today to discuss your specific requirements and find out how we can help.

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Start Your DevOps Transformation Today

Embark on your DevOps journey with Iguana Solutions and experience a transformation that aligns with the highest standards of efficiency and innovation. Our expert team is ready to guide you through every step, from initial consultation to full implementation. Whether you’re looking to refine your current processes or build a new DevOps environment from scratch, we have the expertise and tools to make it happen. Contact us today to schedule your free initial consultation or to learn more about how our tailored DevOps solutions can benefit your organization. Let us help you unlock new levels of performance and agility. Don’t wait—take the first step towards a more dynamic and responsive IT infrastructure now.

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