This server manages all the other servers in the cluster. With full SSH access, you can directly manage the infrastructure and run your models.
This server performs calculations during model training but is not directly accessible to you. Instead, it receives commands from the Poplar server. Please note that the availability of this server type may vary by location.
The virtual Intelligence Processing Unit (vIPU) service configures M2000/Bow-2000 servers to form a cluster. It plays a role during cluster creation and reconfiguration (e.g., resizing partitions). You can access the vIPU controller via API to manage and rebuild the cluster as needed.
This high-security EU data center features H100 and A100 GPUs, along with InfiniBand support and ultra-low latency. As a result, it’s an ideal choice for compliant, high-performance AI workloads that demand speed and reliability.
This eco-friendly site runs on renewable energy and is specifically optimized for high-density GPU compute. Additionally, it offers optional ultra-fast InfiniBand networking for enhanced performance.
GPUs offer high memory bandwidth and efficient data transfer capabilities, which significantly boost large-scale data processing and manipulation. As a result, data analytics becomes faster and more efficient.
Thanks to their superior performance, GPUs are ideal for compute-intensive tasks such as dynamic programming algorithms, video rendering, and scientific simulations. In particular, they excel at handling workloads that demand high processing power.
Deep learning GPUs are well-suited to handle the high processing demands of deep neural networks and recurrent neural networks. These demands are critical for building complex deep learning models, especially those used in generative AI.
AI training GPUs excel at handling numerous matrix operations and computations simultaneously, thanks to their thousands of processing cores. Moreover, their powerful parallel processing capabilities allow them to complete AI training tasks much faster than traditional CPUs.
NVIDIA's A100 and the cutting-edge H100 are leading solutions in the enterprise GPU space. These high-performance accelerators deliver exceptional power and flexibility for a broad spectrum of AI and HPC applications.
Find answers to some frequently asked questions about AI Infrastructure:
A specialised processor, known as a Graphics Processing Unit (GPU), is designed to speed up complicated calculations, especially those that require parallel processing. As a result, GPUs play a crucial role in high-performance AI workloads, since they can handle multiple operations simultaneously. Consequently, this greatly reduces training and inference times in AI and machine learning tasks.
Whether you choose a virtual machine or a bare metal server, the charges depend on the particular configuration you select. Specifically, storage, memory, and GPU type are key factors that influence pricing. For more details, please visit our AI Infrastructure Pricing Page for comprehensive pricing information.
We provide shared (virtual machine) and dedicated (bare metal) GPU instances. For maximum performance, bare metal servers offer exclusive access to hardware resources. In contrast, virtual machines create isolated environments with resources allotted according to your chosen configuration, though they share physical resources.
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