トゥモロー・ネット Product Lineup

Many companies considering the introduction of AI face the challenge of not knowing which GPU is optimal for their specific applications. NVIDIA GPUs come in various types, and the performance required for AI training and inference can vary significantly. In this instance, we clearly propose the optimal NVIDIA GPUs and recommended server configurations for three different applications: large-scale training, inference, and small-scale inference. Additionally, we offer these at a limited-time special price. From the first steps in utilizing AI to building a robust training infrastructure, we support you in selecting the most suitable GPU server for your needs.

Many people may want to advance the utilization of AI and the verification of RAG and LLM within their companies, but are unable to do so due to the hurdles of introducing GPU servers and infrastructure constraints. This campaign proposes an environment where AI development can be started immediately using NVIDIA DGX Spark, without the need for special equipment. It is compact, quiet, and energy-efficient, making it suitable for placement on a desk. It can be expanded to a maximum of four units, allowing for gradual scaling from PoC to team use and eventually to an AI infrastructure.

The "NVIDIA H200" is a Tensor Core GPU that enhances generative AI and HPC workloads. It provides large-capacity and high-speed memory, driving HPC workloads through scientific computing and accelerating generative AI and large language models (LLMs). When processing LLMs like Llama 2, it improves inference speed by up to 2 times compared to the conventional H100 GPU. Achieving unprecedented performance within the same power profile as the H100 Tensor Core GPU, it offers economic advantages through improved energy efficiency and reduced total cost of ownership (TCO). 【Features】 ■ High performance with large-capacity and high-speed memory ■ Accelerates high-performance computing ■ Dramatically reduces energy efficiency and TCO *For more details, please refer to the related links or feel free to contact us.

The NVIDIA L40 is a GPU that provides advanced visual computing performance for data centers. Equipped with 48 GB of ultra-fast GDDR6 memory, it supports memory-intensive workloads such as data science, simulation, 3D modeling, and rendering. The vGPU software allows for efficient memory allocation to multiple users. Designed using power-efficient hardware and components, it is optimized for 24/7 enterprise data center operations. It features secure boot technology using root of trust. 【Features】 ■ 4th Generation Tensor Cores ■ 3rd Generation RT Cores ■ Large-capacity GPU Memory ■ Data Center Ready *For more details, please refer to the related links or feel free to contact us.

The NVIDIA L4 is a Tensor Core GPU that provides energy-efficient universal acceleration powered by the NVIDIA Ada Lovelace architecture. Designed in a slim form factor, it delivers a cost-effective and energy-efficient solution across all servers, including edge, data centers, and cloud. It offers high throughput and low latency, achieving up to 120 times the AI video performance and up to 99% energy efficiency improvement compared to traditional CPU-based infrastructure. It operates at a low power consumption of 72W in a slim form factor. 【Features】 ■ Experience the performance of real-time AI video pipelines ■ Reduce power consumption and installation space with L4 ■ Accelerate generative AI performance ■ Optimize graphics performance ■ Efficiently and sustainably accelerate workloads ■ Streamline development and deployment with enterprise AI software *For more details, please refer to the related links or feel free to contact us.

In the development process of AI applications, the learning phase requires a significant amount of GPU resources. To develop AI applications with higher accuracy in the future, it is necessary to handle an even larger volume of data, and the resources required for the learning time are enormous. Optimizing the utilization of a large number of GPU servers can be considered the most critical issue in AI application development. Federator.ai GPU Booster maximizes the efficiency of GPU utilization during the AI learning phase through its unique AI technology, solving many challenges.