AIME G400 - Workstation
The perfect multi GPU workstation for deep learning and machine learning development. Train your Tensorflow and Pytorch models with up to 4 times the performance of a single high end GPU. Have more then 2000 Tera Tensor FLOPS of AI performance within a HPC AI workstation.
AIME G400 - Deep Learning Workstation
The AIME G400 is designed as maintainable high-end workstation with enough cooling and PSU capacity to host up to four high-end GPUs.
The case is designed for an optimal air flow wich is backed by powerfull, temperature controlled high air flow fans which keep the GPUs and CPU on the optimal operating temperature.
CPU and GPUs directly exhaust the hot air outside of the case to prevent building up heat inside the case. This prevents overheating of the GPU array and maintain high performance under full load in 24/7 scenarios.
Definable GPU Configuration
Choose the desired configuration among the most powerful NVIDIA GPUs for Deep Learning and Rendering:
Up to 4x NVIDIA RTX 6000 Ada
The RTX ™ 6000 Ada is built on the latest NVIDIA GPU architecture: Ada Lovelace. It is the direct succesor of the RTX A6000 and the Quadro RTX 6000. The RTX 6000 Ada combines 568 fourth-generation Tensor Cores, and 18.176 next-gen CUDA® cores with 48GB of graphics memory for unprecedented rendering, AI, graphics, and compute performance.
Up to 2x NVIDIA RTX 4090
The Geforce RTX ™ 4090 is the flagship of NVIDIA Geforce Ada Lovelace GPU generation. It is the direct succesor of the RTX 3090. The RTX 4090 enables 512 fourth-generation Tensor Cores, and 16.384 next-gen CUDA® cores with 24GB of graphics memory for unprecedented rendering, AI, graphics, and compute performance. Due to the tripple level fan architecture the noise level of the RTX 4090 is probably the most suitable solution for running such powerfull GPUs in an office environment.
Up to 4x NVIDIA RTX A6000
The NVIDIA RTX A6000 is the Ampere-based successor to the NVIDIA Quadro series. It features the same GPU processor (GA-102) as the RTX 3090, but all cores of the GA-102 processor are enabled. It outperforms the Geforce RTX 3090 with its 10752 CUDA and 336 Gen 3 Tensor cores. Equipped with 48 GB GDDR6 ECC, twice the amount of GPU memory compared to the predecessor of the Quadro RTX 6000 and the RTX 3090, it is best suited for memory demanding tasks.
Up to 4x NVIDIA RTX A5000
With its 8.192 CUDA and 256 Tensor cores of the 3rd generation, the NVIDIA RTX A5000 is similair powerful than a RTX 3090. However, with its 230 watts of power consumption and 24 GB of memory, it is a more efficient accelerator card and especially for inference tasks the RTX A5000 is a very interesting option.
All NVIDIA GPUs are supported by NVIDIA’s CUDA-X AI SDK, including cuDNN, TensorRT which power nearly all popular deep learning frameworks.
Threadripping Pro CPU Performance
The high-end AMD Threadripper Pro CPU designed for workstations and servers delivers up to 64 cores with a total of 128 threads per CPU with an unbeaten price performance ratio.
The available 128 PCIe 4.0 lanes of the AMD Threadripper Pro CPU allow highest interconnect and data transfer rates between all GPUs and the CPU.
A large amount of available CPU cores can improve the performance immensely in case the CPU is used for tasks like prepossessing and delivering of data to optimal feed the GPUs with workloads.
Up to 16 TB High-Speed SSD Storage
Deep Learning is most often linked to high amount of data to be processed and stored. A high throughput and fast access time to the data are essential for fast turn around times.
The AIME G400 can be configured with up to two 8 TB PCIe 4.0 NVMe SSDs, which are connected by PCIe lanes directly to CPU and main memory with up to 6000 MB/s read, 5000 MB/s write rates.
Additional up to 4 x 16 TB SATA HDDs can be added to the system as backup storage.
A Workstation suitable for Office and Server Room
The AIME G400 was designed as an office compatible PC workstation with server grade hardware. We recommend to limit the configuration with a maximum of two GPUs for use in an office environment.
When setup in an air ventilated dedicated server room the use of up to four GPUs with no restraints is possible. The G400 supports IPMI LAN and a BMC (Board Management Controller) to remote control and monitor the hardware, essential for serious server setups.
Well Balanced Components
All of our components have been selected for their energy efficiency, durability, compatibility and high performance. They are perfectly balanced, so there are no performance bottlenecks. We optimize our hardware in terms of cost per performance, without compromising endurance and reliability.
Tested with Real Life Deep Learning Applications
The AIME G400 was first designed for our own deep learning application needs and evolved in years of experience in deep learning frameworks and customized PC hardware building.
Our machines come with preinstalled Linux OS configured with latest drivers and frameworks like Tensorflow, Keras, PyTorch and mxnet. Just login and start right away with your favourite Deep Learning framework.
AIME G400 Technical Details
3995WX (64 cores, 4.2 GHz) or
5955WX (16 cores, 4.5 GHz) or
5965WX (24 cores, 4.5 GHz) or
5975WX (32 cores, 4.5 GHz) or
5995WX (64 cores, 4.5 GHz)
|64 to 512 GB DDR4 3200 MHz ECC
Up to 2x NVIDIA RTX 4090 24 GB Tripple Fan or
Up to 4x NVIDIA RTX A5000 24 GB or
Up to 4x NVIDIA RTX A6000 48 GB or
Up to 4x NVIDIA RTX 6000 Ada 48 GB
|CPU and GPU high air flow cooled
4 in case high power fans > 100000h MTBF
2 rear high power fans > 100000h MTBF
|Up to 2x 8TB M.2 NVMe SSD PCIe 4.0
7000 MB/s read, 5000 MB/s write
4x 3,5" SATA HDD/SSD bays hot plug (front)
2 x 10 GBit LAN RJ56 (Intel X550)
1 x 1 x GbE LAN RJ45
1 x IPMI LAN RJ 45
Realtek ALC4080 7.1 Surround Sound HD
3 ports Audio Jack (Audio in/Audio out/Mic)
2 x USB 3.0 Type-A
1 x USB 3.2 Gen 2 Type-C
1 x USB 3.2 Gen 2 Type-A
4 x USB 3.2 Type-A
2 x 2000 Watt redundant PSUs
80 PLUS Platinum certified (94% efficiency)
|Idle < 50dBA, Full Load < 80 dBA
|Operation temperature: 10℃ ~ 30℃
Non operation temperature: -40℃ ~ 60℃
|175 x 438 x 680 mm