AI Acceleration
Optimized hardware and software for deep learning inference at the edge
Edge AI requires more than just adding a GPU to a computer. Our platforms are specifically optimized for AI inference workloads with careful attention to memory bandwidth, I/O throughput, and power efficiency. We support major AI frameworks and provide reference implementations for common computer vision and natural language processing tasks.
Key Benefits
Support for NVIDIA, Intel, and Google AI accelerators
Optimized drivers and frameworks for inference performance
Pre-configured AI development environments
Reference implementations for common use cases
Multi-accelerator support for scaling performance
Comprehensive software support and documentation
Technical Deep Dive
GPU Acceleration
Support for NVIDIA RTX and professional GPUs enables high-throughput deep learning inference. Our thermal designs accommodate GPU TDP up to 350W while systems remain passively cooled. PCIe Gen 4 x16 interfaces ensure maximum bandwidth for data transfer to/from GPU memory.
Framework Support
Pre-validated support for TensorFlow, PyTorch, ONNX Runtime, and TensorRT. We provide Docker containers with optimized framework builds and example models for object detection, segmentation, and classification tasks. Integration with MLOps tools simplifies model deployment and updates.
Multi-Accelerator Architecture
High-end platforms support multiple GPU cards or combinations of GPU, VPU, and TPU accelerators. This enables heterogeneous computing where different models run on optimal hardware, or load balancing across multiple inference engines for maximum throughput.
Performance Optimization
Beyond raw compute power, our systems optimize the entire inference pipeline including data ingestion, preprocessing, inference, and post-processing. High-bandwidth networking, NVMe storage, and sufficient system RAM ensure GPU utilization remains high without I/O bottlenecks.
Applications
Real-time video analytics and object detection
Autonomous vehicle perception systems
Quality inspection and defect detection
Natural language processing at the edge
Facial recognition and biometric authentication
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