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Deep learning gpus have been raising the bar on AI and machine learning. They allow users to train networks with far more data and computing power than ever. Supermicro is a company that has been providing industrial-grade barebone servers (a collection of individual components) for data centers.

Supermicro offers a vast selection of server motherboards, memory, storage devices, network cards, and other accessories. They have servers in the market at all different price points to serve your needs, and their expertise in system design ensures that they are optimized for performance while offering security against attacks.

The Supermicro SuperServer 2029P-HC0TR supports NVIDIA Tesla V100 GPU. This GPU is built to deliver the best performance, fast FP16, and FP32 computing, and ease of programming for deep learning and AI. In addition to having a strategic relationship with NVIDIA, Supermicro is certified by multiple cloud providers like Alibaba Cloud, Amazon Web Services (AWS), Microsoft Azure, Tencent Cloud, and Yandex.

Deep Learning Gpus

Supermicro’s 2U low-profile SuperServer 2029P-HC0TR supports a single NVIDIA Tesla V100 GPU, enabling you to develop and deploy machine learning solutions for deep learning and AI based on the latest NVIDIA Volta architecture. It is ideal for various applications such as high-performance computing (HPC), artificial intelligence (AI), software development, big data, virtual reality, and others. The Tesla V100 GPU is PCIe 3.0 x16-based dual-slot card with four 3D NVLink bridges that enables a higher bandwidth between the CPU and GPU than standard PCIe interfaces.

Supermicro’s Expertise

Supermicro has been providing barebone servers to the data center industry for over 20 years and has built a reputation for being the high-performance server leader. With more than 6,000 workers and about $4.5 billion in annual revenue, Supermicro is located in San Jose, California, and produces high-quality, reliable systems. Deep Learning Gpus has been one of their main recent focus, and their latest data centers directly integrate their SR1224F, SR1525F, and SR1608N PCIe NVMe SSDs. In addition to their focus on the data center, they offer barebone servers aimed at the home user with either their SuperServer SYS-E200-8D and SSG-5024 or their SuperBlade 400 product families.

This publication introduces the Supermicro SR1224F and SR1525F NVMe PCIe SSDs. They are designed for high-performance computing (HPC) and artificial intelligence (AI) applications. The follow on feature is a comparison of the PCIe 3.0 x16 vs. 16 PCIe NVMe SSDs from other vendors, as well as some of our custom designs, including our dual M2 NVMe PCIe SSDs that we have been using in our data centers. The deep learning gpus feature introduces the Tesla V100 GPU.

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The Tesla V100 GPU uniquely supports a new acceleration mode (NVLink) that enables the GPU to communicate with 16 M2 PCIe NVMe SSDs in a single PCIe x16 slot and share all data between CPUs and GPUs. It allows users to configure their servers with a single X16 PCIe x16 slot for GPUs, separate X4 PCIe x4 slots for CPU, two dual M2 slots for NVMe SSDs, and two X1 slots for high-speed devices that can operate simultaneously on multiple lanes to boost overall bandwidth.

Supermicro comes with a variety of NVMe PCIe SSD offerings. The SR1224F supports up to 36 TB of data capacity in a 2U Super Server chassis. The SR1525F supports up to 72 TB of data capacity in a 3U SuperServer enclosure. Both SSDs support IOPS and user mode commands (UMC), such as paging, but the SR1525 shares its memory with its GPU and has less cache than the SR1224F. The SR1224F is targeted for high-performance AI, HPC, and deep learning applications. The SR1525F is targeted for HPC/AI applications where minimizing memory requirements, and IOPS performance is essential, while the SR1224F is targeted for deep learning gpus.

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