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Procyon AI Image Generation Benchmark

Benchmarking tool for measuring on-device AI accelerator inference performance.

#AI
#image generation
#Benchmark
#Performance evaluation
#professional user
Procyon AI Image Generation Benchmark

Product Details

Procyon AI Image Generation Benchmark is a benchmark tool developed by UL Solutions to provide professional users with a consistent, accurate, and easy-to-understand workload for measuring the inference performance of on-device AI accelerators. The benchmark was developed in collaboration with multiple key industry members to ensure fair and comparable results across all supported hardware. It includes three tests that measure performance from low-power NPUs to high-end discrete graphics cards. Users can configure and run through the Procyon application or the command line, supporting multiple inference engines such as NVIDIA® TensorRT™, Intel® OpenVINO™ and ONNX with DirectML. The product is intended primarily for engineering teams and is suitable for evaluating general-purpose AI performance on inference engine implementations and specialized hardware. In terms of price, a free trial is provided, and the official version is an annual venue license. You need to pay to get a quote.

Main Features

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Provides a series of tests centered around image generation workloads, using state-of-the-art neural networks.
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Designed to measure the inference performance of various AI accelerators.
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Supports inference engines such as NVIDIA® TensorRT™, Intel® OpenVINO™ and ONNX with DirectML.
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Verify inference engine implementation and compatibility.
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Simple to set up and use via the Procyon app or command line.
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Multiple versions of the Stable Diffusion AI model are available for testing.
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Compare up to 4 results side by side within the app.

How to Use

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1. Visit https://benchmarks.ul.com/procyon/ai-image-generation-benchmark page for product details.
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2. Choose a free trial or get a quote for the official version according to your needs.
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3. Download and install the Procyon application.
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4. Configure test parameters through the application, such as selecting inference engine, test version, etc.
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5. Run the benchmark test and the application will automatically execute the testing process.
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6. After the test is completed, view the generated report, including overall score, detailed score, generated images, etc.
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7. Carry out hardware selection or performance optimization based on test results.

Target Users

The target audience is engineering teams and professional users who need independent, standardized tools to evaluate the general AI performance of inference engine implementations and specialized hardware to make accurate decisions during product development and performance evaluation.

Examples

Hardware manufacturers use this benchmark to evaluate and optimize the performance of their AI accelerators.

Software developers use the test results to choose the inference engine best suited for their applications.

Scientific research institutions use benchmark tests to compare the AI ​​reasoning capabilities of different hardware platforms.

Quick Access

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› AI model
› Development and Tools

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