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We at HOSTKEY now have on offer a wide range of last-gen servers ideal for any number of tasks requiring accelerated computing including HPC and AI. In an effort to make finding the right server easy, HOSTKEY has introduced a GPU server class system geared towards helping you choose for specific applications: Supercomputing (SCX), Inference (HGX-I), and Training (HGX-T). Our offerings also include cheap GPU for deep learning, making it an ideal choice for those looking for a deep learning server. As a provider of machine learning servers, we take into account the whole data-center ecosystem, and as such you can rest assured that when you make the choice of a specific GPU-accelerated server platform, it will deliver the maximum performance possible for the job at hand.
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Fully customizable dedicated and instant virtual servers with NVIDIA RTX 4000 / 5000 / A6000 GPU cards
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Virtual (VPS/VDS) and dedicated GPU servers with RTX A4000 / A5000 / A6000 GPU cards
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Fully customizable dedicated and instant virtual servers with NVIDIA RTX 4000 / 5000 / A6000 GPU cards
NL
Virtual (VPS/VDS) and dedicated GPU servers with RTX A4000 / A5000 / A6000 GPU cards
Please check our pre-configured GPU server section to reveal more CPU options.
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These are servers that use the advanced computing capabilities of GPUs to assist in calculations that require multi-dimensional training. When using GPU servers in deep learning methods, the training of various models will be significantly improved. Moreover, GPU servers can perform complex and accurate computations for any task.
Innovative video cards from NVIDIA are suitable for deep learning — RTX 4090, A100, H100, A5000.
Unlike CPU-based systems, GPU processing has major advantages because it performs parallelizable tasks well based on its specific hardware architecture. This is in contrast to the four or five powerful cores in a traditional CPU that are optimized for serial processing. The GPU’s many cores allow it to break down complex relationships into simpler sub-relationships and process them simultaneously.
Although CPUs are critical for sequential tasks and system orchestration, there is an opportunity to significantly reduce the time usage for tasks that can be executed in parallel using GPUs. The main advantage is the ability of GPUs to process several thousand threads simultaneously. Large amounts of data are processed instantly.
Yes, low cost GPU for deep learning supports innovative frameworks for high-quality work with artificial intelligence.
HOSTKEY equips low cost GPU for deep learning with NVMe SSD storage and 32 to 128 gigabytes of RAM.
Yes, HOSTKEY provides you with such an opportunity. Enjoy the extensive functionality of deep learning gpu server.
We use DDoS protection using software and hardware solutions to protect against TCP-SYN Flood attacks (SYN, ACK, RST, FIN, PUSH), and host servers in TIER III data centers.
To increase the power of gpu servers for machine learning, contact HOSTKEY managers for help. They will quickly increase the capabilities of your server.
Yes, you can use such services in HOSTKEY — it will help you save your data.
HOSTKEY offers to rent GPU VPS at a great price. Our offers are well suited for solving machine learning tasks. Each tariff plan is provided with basic protection against DDoS attacks. We guarantee stable operation of your projects and solution of any tasks.
HOSTKEY provides a large selection of GPU servers for deep learning. They work stably and show good results.
HOSTKEY uses only innovative and powerful video cards in deep learning GPU servers:
High-Performance NVIDIA GPUs (RTX 4090, A100, H100, A5000)
The servers maintain state-of-the-art NVIDIA GPUs which optimize deep learning operations as well as artificial intelligence functions and high-performance computing (HPC) processes. The GPUs deliver outstanding FP32 and FP16 performance throughput which permits both speedier training and inference operations for difficult neural network programs. The servers enable mixed-precision Tensor Core calculations and parallel programming through CUDA optimizations.
The core supports TensorFlow, PyTorch and JAX AI/ML framework operation.
The infrastructure operates perfectly with industry normal machine learning frameworks while delivering advanced software capabilities along with enhanced driver performance. cuDNN and TensorRT form part of pre-optimized GPU acceleration libraries that provide maximum performance for both model training and inference processes and extensive AI computations.
Low-Latency, High-Speed Networking for Distributed Training
Users can optimize distributed deep learning operations by using servers with RDMA over Converged Ethernet (RoCE) and InfiniBand interfaces that deliver rapid communication at high speed. These infrastructure characteristics minimize GPU-to-GPU network transfers thus speeding up simultaneous training operations in multiple computing nodes.
Configurations for Any Requirement
GPU instance scaling provides full flexibility to add or reduce resources automatically according to changing workload requirements. Users can select either a standalone GPU system or a multi-GPU cluster ensemble equipped with NVLink or PCIe data transfer technology for maximum speed. Management tools for automatic scaling allow users to optimize costs and maintain high performance alongside each other.
24/7 Support
Our servers operate with mission-critical AI applications and contain redundant power supply systems along with ECC memory to protect data and automatic hardware monitoring systems. The 24/7 enterprise support team stands ready to help customers immediately which leads to reduced downtime and peak system performance that ensures continuous deep learning operations.
If you choose GPU servers for machine learning in HOSTKEY, you are guaranteed to receive the following benefits:
1. VDS with GPU (Iceland)
2. Dedicated GPU Server (Netherlands)
3. Dedicated GPU Server (Iceland)
4. VDS with GPU (Iceland)
5. VDS with GPU (Netherlands)
6. Dedicated GPU Server (Netherlands)
7. Dedicated GPU Server (Netherlands)
GPU servers for deep learning are used in various modern projects:
In order to rent GPU servers for deep learning, you need to:
| Location | Server type | GPU | Processor Specs | System RAM | Local Storage | Monthly Pricing | 6-Month Pricing | Annual Pricing | |
|---|---|---|---|---|---|---|---|---|---|
| NL | Dedicated | 1 x GTX 1080Ti | Xeon E-2288G 3.7GHz (8 cores) | 32 Gb | 1Tb NVMe SSD | €170 | €160 | €150 | |
| NL | Dedicated | 1 x RTX 3090 | AMD Ryzen 9 5950X 3.4GHz (16 cores) | 128 Gb | 480Gb SSD | €384 | €327 | €338 | |
| RU | VDS | 1 x GTX 1080 | 2.6GHz (4 cores) | 16 Gb | 240Gb SSD | €92 | €86 | €81 | |
| NL | Dedicated | 1 x GTX 1080Ti | 3.5GHz (4 cores) | 16 Gb | 240Gb SSD | VDS | €94 | €88 | €83 |
| RU | Dedicated | 1 x GTX 1080 | Xeon E3-1230v5 3.4GHz (4 cores) | 16 Gb | 240Gb SSD | €119 | €112 | €105 | |
| RU | Dedicated | 2 x GTX 1080 | Xeon E5-1630v4 3.7GHz (4 cores) | 32 Gb | 480Gb SSD | €218 | €205 | €192 | |
| RU | Dedicated | 1 x RTX 3080 | AMD Ryzen 9 3900X 3.8GHz (12 cores) | 32 Gb | 480Gb NVMe SSD | €273 | €257 | €240 |
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