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Untether tsunAImi tsn200ES Accelerator

The runAI200™ accelerator is designed for real-time deep learning inference and high-performance computing (HPC) applications. Its unique at-memory architecture combines over 260,000 processing elements, 511 custom RISC-V processors, and 204 MB of SRAM into the industry’s most efficient chip in its class, delivering 8 TOPs/W. The imAIgine™ software development kit (SDK) enables push-button performance on deep learning networks in standard frameworks and a custom kernel development flow for high-performance computing applications that require arbitrary computation.

tsunAImi accelerator card from untether AI


  • 502 INT8 TOPs
  • 204MB on-chip SRAM
  • 75W TDP 40W typical
  • 8 TOPs/W
  • At-Memory Architecture
  • Scalable voltage and frequency
  • Low latency, native batch = 1 PCIe Gen4 x16


The runAI200 devices are designed to accelerate a multiplicity of AI inference and HPC workloads, such as vision-based convolutional networks, transformer networks for natural language processing, time-series analysis for financial applications, and general-purpose linear algebra for high-performance computing applications.

VisionClassification, object detection, semantic segmentationResNets, YOLO, SSD, Unets, Pose
Natural language processingText-to-speech, speech-to-text, chatbotsRNNs, Transformers, BERT
Financial technologyX-Value adjustments, credit risk, portfolio balancingTCNs, LSTMs
HPCClimate modelling, deep packet inspection, simulationsFFTs, BLAS, arbitrary computation

imAIgine Software Development Kit

The imAIgine SDK gives developers powerful automated tools and supporting software to quickly go from the pilot model to production. It is organized into three parts.

  • The imAIgine Compiler
    • Import TensorFlow, PyTorch, or ONNX graphs directly
    • Automated quantizer and extracts performance without sacrificing accuracy
    • Specify performance levels, silicon utilization, and power consumption targets
  • The imAIgine Toolkit
    • Evaluate functionality and performance using the extensive profiling and simulation tools
  • The imAIgine Runtime
    • Provides C-based API for integration into your deep learning environment
    • Monitor the health and temperature of the tsunAImi® acceleration cards to ensure proper operation and prevent thermal damage


Contact Us

Dr. Yassine Hariri
Senior Staff Scientist
AI/ML and Embedded Systems

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