Want to accelerate your edge AI workloads? There are many options to get started, whether you’re in early-stage development or ready to go to volume production on a complex module.
Get the SAKURA-I chip on a full-height, single-width PCIe card that's perfect for benchtop development. Includes MERA Compiler Framework and tools, with the DNA neural processing engine, embedded into SAKURA-I.
Includes MERA Compiler Framework and tools, the DNA neural processing engine IP, bundled with BittWare's PCIe accelerator cards featuring Intel Agilex 7 FPGAs. Tap here for more details on this solution.
With a power-efficient ASIC, customized cards or microelectronics modules are a perfect fit.
EdgeCortix SAKURA-I is a TSMC 12nm FinFET co-processor (accelerator) delivering class-leading compute efficiency and latency for edge artificial intelligence (AI) inference. It is powered by a 40 trillion operations per second (TOPS), single core Dynamic Neural Accelerator® (DNA) Intellectual Property (IP), which is EdgeCortix’s proprietary neural processing engine with built-in runtime reconfigurable data-path connecting all compute engines together. DNA enables the new SAKURA-I AI co-processor to run multiple deep neural network models together, with ultra-low latency, while preserving exceptional TOPS utilization. This unique attribute is key to enhancing the processing speed, energy-efficiency, and longevity of the system-on-chip, providing exceptional total cost of ownership benefits. The DNA IP is specifically optimized for inference with streaming and high-resolution data.
EdgeCortix SAKURA-I AI Co-processor enabled devices are supported by the heterogeneous compiler and software framework – EdgeCortix MERA that can be installed from a public pip repository, enabling seamless compilation and execution of standard or custom convolutional neural networks (CNN) developed in industry-standard frameworks. MERA has built-in integration with Apache TVM, and provides simple API to seamlessly enable deep neural network graph compilation and inference using the DNA AI engine in SAKURA-I. It provides profiling tools, code-generator and runtime needed to deploy any pre-trained deep neural network after a simple calibration and quantization step. MERA supports models to be quantized directly in the deep learning framework, e.g., Pytorch or TensorflowLite.
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