#USA #Irvine #AIBooster #Fixstars Corporation #AcuiRT

Fixstars Corporation Unveils Upgraded AIBooster

In a major advancement for the AI industry, Fixstars Corporation, headquartered in Irvine, California, has recently launched updated features for its AI acceleration platform, AIBooster. Known for its innovative performance engineering technology, Fixstars is leading the way in enhancing AI model deployment efficiency across various sectors, including healthcare, finance, and manufacturing.

New Features Introduced

The latest iteration of AIBooster emphasizes enhanced flexibility and sophisticated diagnostics, focusing on optimizing the AcuiRT framework for inference-optimized AI model conversion. This updated platform now boasts customized performance observability coupled with user-defined metrics, allowing engineers to optimize their models with less overhead.

1. Advanced Diagnostic Reports for AcuiRT
The newly improved AcuiRT now equips engineers with significantly advanced diagnostic capabilities, enabling them to address deployment issues more effectively. Users can access comprehensive CLI commands or opt for detailed reports, which present a breakdown of the conversion process. These reports include:
- Conversion Result Visualization: A detailed analysis of conversion successes and failures, layer-by-layer success rates, specific error messages for failed layers, and inference accuracy assessments to expose potential performance degradation.
- Performance Profiling: This tool scrutinizes post-conversion parameters, evaluating inference latency and providing granular insights on each layer's processing time, which assists in identifying performance bottlenecks.

2. Customizable Performance Observability
The observability feature allows users to monitor performance trends across multiple clusters while evaluating hardware efficiency at both the node and device level. The latest version enables users to customize various parameters for a tailored observation experience, such as:
- Metric Collection Intervals: Users can set the frequency of data collection, allowing them to reduce resource consumption for long-term trend analysis.
- User-Defined Tags: These personalized tags enable users to categorize workloads based on specific criteria like model type, execution settings, or datasets. This functionality fosters a deeper performance analysis through unique perspectives.

Practical Application of AIBooster

A real-world example underscores the benefits of the revived AIBooster features. A team optimizing a 2D object detection model (the Detection Transformer DETR) encountered challenges when converting a trained PyTorch model to an NVIDIA GPU-optimized format using AcuiRT.
Despite initial challenges, with only a 16% conversion success rate, the team utilized the new diagnostic report feature to identify issues within the model. After four hours of refactoring based on insights from the reports, the team achieved a full layer conversion. Moreover, they realized an approximate 1.25x improvement in inference speed, showcasing the robust capabilities of the new AIBooster enhancements.

Fixstars’ Commitment

Fixstars Corporation remains dedicated to equipping its customers with state-of-the-art tools essential for high-performance, cost-effective AI operations. These updates ensure clients can execute seamless, efficient AI deployment in diverse environments, keeping pace with the rapid advancements in technology.

Understanding the critical nature of efficient AI operations, Fixstars is focused on overcoming the limitations traditionally faced in AI model conversions and deployments. With a commitment to innovation, the company continues to enhance its suite of solutions for various industries.

For more details about Fixstars’ new offerings or to discover how they can support your AI operations, visit Fixstars' official website.

Media Contact: Public Relations, Fixstars Corporation
Email: [email protected]
Phone: (408) 400-3679