[San Jose, May 31, 2018] Quanta Cloud Technology (QCT), a global data center solution provider, today introduced its latest purpose-built dual-socket Intel®Xeon Scalable accelerator server for AI and HPC computing - the QuantaGrid D52G-4U, currently supporting three different baseboards optimized for different application. First, the D52G-4U supports eight NVIDIA Tesla V100 SXM2 GPU accelerators with maximum GPU-to-GPU 300 GB/s NVLink™ interconnect to deliver extreme training performance to shorten R&D development while adopting deep learning to innovate business models. D52G-4U outperforms on every popular convolutional neural network such as Inception V3 and the more complex Resnet-50 (see Image 1); Furthermore, it also demonstrates 96.2% efficiency while running GoogleNet on eight NVIDIA®Tesla V100's (see image 2). With such high scale up efficiency, the D52G can squeeze the most computing power of multiple GPUs to accelerate training models.
Image 1: Benchmark of D52G-4U on the Tensorflow Deep Learning Framework
Image 2: Benchmarks of the D52G-4U on NvCaffe
Second, the D52G-4U PCIe baseboard provides flexible topology on eight double-width GPU's to optimize either CPU-to-GPU bandwidth or GPU-to-GPU communication to fine tune the performance for different HPC applications to reduce the risk of IT investment. Lastly, after training a model with high accuracy, the key factor to succeed in business innovation is looking at how the pre-trained model can be efficiently delivered to as many users as possible. The D52G-4U baseboard with twenty single-slots can satisfy massive inference demands concurrently with sixteen single slot power efficient GPUs like the NVIDIA Tesla® P4. This SKU also supports high bandwidth low latency Infiniband to scale out the performance and 24 small form factor storage bays with low latency NVMe SSDs to reduce IO reading and to feed large amounts of data to this powerful machine.
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