DEEP LEARNING INFERENCE SOLUTIONS
THE LATEST INFERENCE ACCELERATORS | FULL TURNKEY SOLUTIONS | 3 YEAR WARRANTY & SUPPORT
Exxact Deep Learning Inference Servers
Exxact Deep Learning Inference Servers are optimized for use in image and video search, video analytics, object classification and detection, and a host of other usages.
Exxact Deep Learning Inference Servers cater to real-time use cases involving multiple inferences per query, such as automatic speech recognition, speech to text, natural language processing, and more.
The Turing-based Tesla T4 offers efficiency far exceeding either the Tesla P4 or the Tesla V100. With its small form factor and 70-watt (W) footprint design, it's the perfect GPU for inference solutions.
HIGH PERFORMANCE HARDWARE
From NVIDIA T4 Inference GPUs, or Xilinx FPGA Accelerators, Exxact Inference Solutions meet your most demanding deep learning inference tasks.
GET MORE DONE
Have peace of mind and focus on what matters most, knowing your system is backed by a 3 year warranty and support.
Including TensorRT inference server, which is production-ready and supports multiple frameworks (TensorFlow, Caffe2, TensorRT/TensorFlow, ONNX and custom backends).
Suggested Exxact Deep Learning Inference Systems
Bring AI to the Edge with Exxact Inference Servers & NVIDIA EGX
Communicate with customers in real time. Adapt quickly as data flows from billions of sensors, from factory floors to store aisles. Instantaneously diagnose diseases and provide life-saving patient care. All of this is possible—smart retail, healthcare, manufacturing, transportation, and cities—with today's powerful AI and the NVIDIA EGX platform, which brings the power of accelerated AI computing to the edge.
High Performance and Scalable
NVIDIA EGX is highly scalable, starting from a single node GPU system and scaling all the way to a full rack of NVIDIA T4 servers, with the ability to deliver more than 10,000 TOPS to serve hundreds of users for real-time speech recognition and other complex AI experiences.
Hybrid Cloud and Multicloud IoT
NVIDIA EGX is architecturally compatible with major cloud providers. AI applications developed in the cloud can run on NVIDIA EGX and vice versa. NVIDIA Edge Stack connects to major cloud IoT services, and customers can remotely manage their services.
Enterprise Grade and Secure
NVIDIA Edge Stack has been optimized on Red Hat OpenShift, the leading enterprise-grade Kubernetes container orchestration platform. Mellanox Smart NICs can offload and accelerate software defined networking to enable a higher level of isolation and security without impacting CPU performance.
Enterprise-Grade Software Stack for the Edge
NVIDIA Edge Stack is an optimized software stack that includes NVIDIA drivers, a CUDA® Kubernetes plug-in, a CUDA Docker container runtime, CUDA-X libraries, and containerized AI frameworks and applications, including NVIDIA TensorRT™, TensorRT Inference Server, and DeepStream.
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NVIDIA TensorRT Hyperscale Inference Platform
The NVIDIA TensorRT™ Inference Platform is designed to make deep learning accessible to every developer and data scientist anywhere in the world. Utilizing the new Turing architecture, Tesla T4 accelerates all types of neural networks for images, speech, translation, and recommendation systems. Tesla T4 supports a wide variety of precision and accelerates all major DL frameworks, including TensorFlow, PyTorch, MXNet, Chainer, and Caffe2.
NVIDIA TensorRT optimizer and runtime unlocks the power of Turing GPUs across a wide range of precision, from FP32 down to INT4. In addition, TensorRT integrates with TensorFlow and supports all major frameworks through the ONNX format. NVIDIA TensorRT Inference Server is a production-ready deep learning inference server. It reduces costs by maximizing utilization of GPU servers and saves time by integrating seamlessly into production architectures.
For large-scale, multi-node deployments, Kubernetes enables enterprises to scale up training and inference deployment to multi-cloud GPU clusters seamlessly. It allows software developers and DevOps engineers to automate deployment, maintenance, scheduling, and operation of multiple GPU-accelerated application containers across clusters of nodes. With Kubernetes on NVIDIA GPUs, they can build and deploy GPU-accelerated deep learning training or inference applications to heterogeneous GPU clusters and scale seamlessly.
Exxact Deep Learning Inference Servers Maximize Performance Efficiency
Exxact Deep Learning Inference Servers powered by NVIDIA Tesla T4 GPUs bring revolutionary multi-precision inference performance to efficiently accelerate the diverse applications of modern AI. In addition, the Tesla T4 greatly outperforms its predecessor, the Tesla P4.
System configs: Xeon Scalable Processor Gold 6140 @ 3.7 GHz and a single Tesla P4 or V100: Tesla GPUs running TensorRT 126.96.36.199, Telsa T4 (pre-production) running TensorRT 5RC: CPU running Intel OpenVINO 2018 R2: batch size 128: recision: FP32 for CPU, Mixed precision (FP16 compute/ FP32 accumulate) for V100, INT8, for P4 and T4
Deep Learning Training vs Deep Learning Inference:
Which GPU is right for me?
The T4 is truly groundbreaking for performance and efficiency for deep learning inference. But how does it stack up for deep learning training? Just because you can train on a T4, it doesn't mean you should. If your goal is training deep neural networks we recommend using NVIDIA Tesla V100 GPUs, and the numbers below (courtesy NVIDIA) back that up.
RESNET-50 IMAGE TRAINING
NVIDIA TESLA V100 AND NVIDIA TESLA T4
However, If your deep learning inference is your primary workload, the NVIDIA T4 is a better choice.
RESNET-50 INFERENCE LATENCY
RESNET-50 POWER EFFICIENCY
DGX-1: 1X Tesla V100-SXM2-16GB, E5-2698V4 2.2 GHz | TensorRT 5.0 | Batch Size = 1 | Precision: INT8 | Dataset: Synthetic. Supermicro SYS-4029GP-TRT T4: 1x Tesla T4, Gold 6140 23. GHz | TensorRT 5.0 | Batch Size: = 1| Precision: INT8 | Dataset: Synthetic
Use Cases for Inference Solutions
SELF DRIVING CARS
INTELLIGENT VIDEO ANALYTICS
- Rack Height: 2U
- Processor Supported: 2x Intel Xeon Scalable Family
- Drive Bays: 8x 3.5" Hot-Swap (2x NVMe)
- Supports up to 4x Double-Wide cards
- Rack Height: 4U
- Processor Supported: 2x Intel Xeon Scalable Family
- Drive Bays: 24x 3.5" Hot-Swap
- Supports up to 20x NVIDIA Tesla T4 GPUs
- Form Factor: 4U Rackmountable / Tower
- Processor: 2x Intel Xeon Scalable family
- Drive Bays: 4x 3.5"/2.5" Hot-Swap
- Up to 5x Double-Wide cards