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MERA Compiler and Software Framework

Fast and Easy Model Porting and System Integration

Supported Frameworks & Applications

MERA Compiler and Software Framework

EdgeCortix® MERA is a compiler and software framework providing a robust platform for deploying the latest neural network models in a framework agnostic manner. MERA enables deep neural network graph compilation and AI inference using the Dynamic Neural Accelerator (DNA) and provides the necessary tools, APIs, code-generator, and runtime needed to deploy a pre-trained deep neural network.

MERA is designed to handle the most challenging Generative AI applications at the edge, enabling designers to create new content for use in Vision, Language, Audio, and many other applications.

With MERA’s built-in heterogeneous support for leading processors, including AMD, Intel, Arm, and RISC-V, it is fast and easy to integrate the EdgeCortix AI platform into existing systems. Pre-defined and optimized models can be directly sourced from Hugging Face or EdgeCortix Model Library, followed by calibration and quantization. MERA offers software developers and data scientists familiar workflows for developing these models without dealing with chip-level hardware architecture. MERA leverages Apache TVM and MLIR functionality, and its front end is open sourced for easy distribution to project teams.

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Integrated in familiar AI inference workflows

MERA provides the entire stack for edge AI inferencing from modeling to deployment with familiar neural network model workflows and supports easy integration with existing systems, reducing time-to-market. MERA is optimized for the latest vision and Generative AI models with market-leading energy efficiency and low latency in combination with SAKURA-II.

MERA is a compiler and software framework enabling deep neural network graph compilation and AI inference using the Dynamic Neural Accelerator (DNA). MERA provides the necessary tools, APIs, code-generator and runtime needed to deploy a pre-trained deep neural network after a simple calibration and quantization step.

MERA Key Benefits

  • Source pre-defined and optimized models from Hugging Face and the EdgeCortix Model Library
  • Generative AI Models - Llama-2, Stable Diffusion, Whisper, DETR, DistillBert, DINO and ViT
  • Supports Python and C++ interfaces for workflow integration and customization
  • Native support for ML frameworks PyTorch, TensorFlow Lite, and ONNX
  • Post-training calibration and quantization of user-defined models
  • Stand-alone estimation of inference latency and throughput

Everything needed for AI inference development and deployment

  • Runtime configuration of DNA
  • Simulation and profiling for stand-alone use
  • Low-level IR (Intermediate Representation)
  • Host processor code generation
  • High-level graph partitioning
  • APIs for popular machine learning frameworks
  • Model calibration and quantization
  • Pre-trained applications in the Model Library
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MERA Software Supports Diverse Neural Networks from Convolutions to the Latest Generative AI Models

Example Models Include:
Transformer Models Convolutional Models
DETR
DINO
Whisper Encoder / Decoder
DistillBERT
DistilBert - SST2
Nano-GPT
GPT-2 - 150M
Distil-GPT-2 (HF)
GPT-2 (HF) - 117M
GPT-2 (HF) - medium / large
GPT-2 - XL (HF) - 1.5B
TinyLama (HF) - 1.1B
Phi-2 (HF) - 3B
Open-Llama2 (HF) - 7B
CodeLlama (HF) - 7B
Mistral-v0.2 (HF) - 7B
Llama3 - 8B
ViT (HF) / CLIP / Mobile-ViT
ConvNextV1/V2 (HF)
SegFormer
Roberta-Emotion
StableDiffusion V1.5
ResNet 18
ResNet 50/101
Big YoloV3
TinyYolo V3
Yolo V5/V6/V8
YoloX
EfficientNet-Lite
EfficientNet-V2
SFA3D
MonoDepth - MiDaS
U-Net
MoveNet
DeepLab
MobileNet V1-V2
MobileNetV2-SSD
GladNet
ABPN
SCI
Example Models Include:
Transformer Models
DETR
DINO
Whisper Encoder / Decoder
DistillBERT
DistilBert - SST2
Nano-GPT
GPT-2 - 150M
Distil-GPT-2 (HF)
GPT-2 (HF) - 117M
GPT-2 (HF) - medium / large
GPT-2 - XL (HF) - 1.5B
TinyLama (HF) - 1.1B
Phi-2 (HF) - 3B
Open-Llama2 (HF) - 7B
CodeLlama (HF) - 7B
Mistral-v0.2 (HF) - 7B
Llama3 - 8B
ViT (HF) / CLIP / Mobile-ViT
ConvNextV1/V2 (HF)
SegFormer
Roberta-Emotion
StableDiffusion V1.5
Convolutional Models
ResNet 18
ResNet 50/101
Big YoloV3
TinyYolo V3
Yolo V5/V6/V8
YoloX
EfficientNet-Lite
EfficientNet-V2
SFA3D
MonoDepth - MiDaS
U-Net
MoveNet
DeepLab
MobileNet V1-V2
MobileNetV2-SSD
GladNet
ABPN
SCI

SAKURA-II M.2 Modules and PCIe Cards

EdgeCortix SAKURA-II can be easily integrated into a host system for software development and AI model inference tasks.

Pre-Order an M.2 Module or a PCIe Card and get started today!

EdgeCortix Edge AI Platform

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Dynamic Neural Accelerator® Technology
Flexible, run-time reconfigurable, highly-parallelized and efficient architecture

Proprietary Architecture
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SAKURA™ AI Accelerator
High Performance, Low Power, Generative AI ready, effectively handles multi-billion parameter models

Efficient Hardware
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AI Accelerator Modules and Cards
Up to 240 TOPS in systems powered by the latest SAKURA-II AI Accelerators

Deployable Systems
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Given the tectonic shift in information processing at the edge, companies are now seeking near cloud level performance where data curation and AI driven decision making can happen together. Due to this shift, the market opportunity for the EdgeCortix solutions set is massive, driven by the practical business need across multiple sectors which require both low power and cost-efficient intelligent solutions. Given the exponential global growth in both data and devices, I am eager to support EdgeCortix in their endeavor to transform the edge AI market with an industry-leading IP portfolio that can deliver performance with orders of magnitude better energy efficiency and a lower total cost of ownership than existing solutions."

Akira Takata
Former CEO of MegaChips Corporation
SoftBank

Improving the performance and the energy efficiency of our network infrastructure is a major challenge for the future. Our expectation of EdgeCortix is to be a partner who can provide both the IP and expertise that is needed to tackle these challenges simultaneously."

Ryuji Wakikawa
Head, Research Institute of Advanced Technology at SoftBank Corp
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With the unprecedented growth of AI/Machine learning workloads across industries, the solution we're delivering with leading IP provider EdgeCortix complements BittWare's Intel Agilex FPGA-based product portfolio. Our customers have been searching for this level of AI inferencing solution to increase performance while lowering risk and cost across a multitude of business needs both today and in the future."

Craig Petrie
VP, Sales and Marketing at BittWare
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EdgeCortix is in a truly unique market position. Beyond simply taking advantage of the massive need and growth opportunity in leveraging AI across many business key sectors, it’s the business strategy with respect to how they develop their solutions for their go-to-market that will be the great differentiator. In my experience, most technology companies focus very myopically, on delivering great code or perhaps semiconductor design. EdgeCortix’s secret sauce is in how they’ve co-developed their IP, applying equal importance to both the software IP and the chip design, creating a symbiotic software-centric hardware ecosystem, this sets EdgeCortix apart in the marketplace.”

DANIEL FUJII
President & CEO of Trust Capital Co., Ltd., member of the Executive Committee of Silicon Valley Japan Platform
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We recognized immediately the value of adding the MERA compiler and associated tool set to the RZ/V MPU series, as we expect many of our customers to implement application software including AI technology. As we drive innovation to meet our customer's needs, we are collaborating with EdgeCortix to rapidly provide our customers with robust, high-performance and flexible AI-inference solutions. The EdgeCortix team has been terrific, and we are excited by the future opportunities and possibilities for this ongoing relationship."

Shigeki Kato
Vice President, Enterprise Infrastructure Business Division

EdgeCortix Business Summary

Maximizing Business Value with Energy Efficient Generative Edge AI Solutions

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