New Products

Large AI model parameters have grown exponentially in scale, from the hundreds of billions to trillions. Training sets have also evolved from unimodal to multi-modal (images, videos, etc.) paradigms, resulting in a data explosion that has increased volumes by thousands, and brought unprecedented challenges.
First, poor loading performance among massive numbers of small files has undermined training efficiency.
Second, large model parameters are frequently being optimized, which has led to unstable training platforms, with service interruptions occurring every two days on average, and frequent, time-consuming read and write of TB-level checkpoints.
Third, training 100-billion-parameter models requires massive GPU resources, since individual GPUs are not efficient enough, and ensuring millisecond-level real-time inference for conversational applications is quite challenging.

OceanStor A800 delivers a staggering 24 million IOPS and 500 GB/s bandwidth within a single controller enclosure, serving as the high-performance AI storage solution. With four times the performance of the next runner-up, a single storage system is all you need for small file loading of training sets and high-bandwidth-based resumable training. You'll also benefit from access to a leading intrinsic vector knowledge repository, which supports large model inference applications with over 15,000+ QPS, achieving accelerated vector retrieval and millisecond-level inference response.

The NetEngine 8000 F2C is a high-density fixed-configuration router designed for the cloud era. This all-service router mainly functions as a P or PE node with a forwarding capacity of 7.2 Tbps. It provides high-density 100GE/400GE interfaces with flexible switching between 100GE and 400GE. Compact at only 2U high and 442 mm deep, this router helps saves equipment room space, slash CAPEX, and protect existing investments, making it the best choice for high-density transport in the cloud era.