You can choose package products equipped with NVIDIA GPUs optimized for everything from large-scale AI training to small-scale AI inference!
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.
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basic information
【H200 Configuration】 System: AS -8125GS-TNHR CPU: AMD EPYC 9534 64Core 2.45GHz x2 Memory: 96GB DDR5 5600 ECC REG x24 SSD: 2.5" U.2 NVMe 7.6TB x4 GPU: NVIDIA SXM HGX H200 141GB 8-GPU 【RTX PRO 6000 Configuration】 System: SYS-521GE-TNRT CPU: Intel Xeon 4516Y+ 24Core 2.2GHz x2 Memory: 96GB DDR5 5600 ECC REG x8 SSD: 2.5" U.2 NVMe 1.9TB x4 GPU: NVIDIA RTX PRO 6000 Server Edition x4 【L40S Configuration】 System: SYS-521GE-TNRT CPU: Intel Xeon 4514Y 16Core 2.0GHz x2 Memory: 96GB DDR5 5600 ECC REG x8 SSD: 2.5" U.2 NVMe 1.9TB x4 GPU: NVIDIA L40S x4
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Applications/Examples of results
H200 equipped: Large-scale learning server for generative AI and LLMs With high-bandwidth and efficient GPU intercommunication and large-capacity HBM3 memory, it can execute the processing required for training large models such as LLMs and generative AI at high speed. Additionally, equipped with a 64-core EPYC CPU and high-speed NVMe, it is optimally designed for AI development and research applications that handle large datasets, with a well-balanced overall design based on training workloads. RTX PRO 6000 equipped: High-performance server for AI inference Equipped with four RTX PRO 6000s, it can execute inference processing with high efficiency and low latency stably. This configuration is perfect for environments that handle a large number of requests during the operational phase, such as image generation, chat AI, and analytical processing, making it a suitable GPU server for "practical stage AI utilization," including service provision and AI integration into internal systems. L40S equipped: AI inference server for small to medium scale Ideal for the initial phase of AI implementation that does not require excessive performance, such as PoC, internal use, and small-scale image generation and analysis. It is an optimal configuration for those prioritizing cost-effectiveness while wanting to build an AI infrastructure with reduced initial costs.
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Company information
Our company started its business in February 2005 with support services for medical information systems and has since been engaged in providing IT solutions as a system integrator. We cultivate open-minded individuals who can approach their work creatively, and it is these "people" who become the driving force behind our high-value-added services, allowing our clients to experience "passion," "flexibility," and "a sense of speed."
