Introduction to XANI
The XANI workflow is a massive-scale X-ray free-electron laser (XFEL) that enables tracking structural and electron dynamics in novel systems, including fusion materials, semiconducters, batteries, and catalysis. The XANI workflow has been accelerated using AI and NVIDIA technology to process and analyze large amounts of data quickly and accurately. The team accelerated the XANI workflow and compressed the computational time to process and analyze 42 terabytes (TBs) of data from nine months to less than four hours on 32 NVIDIA GB200 Grace Blackwell Superchips, while preserving the same precision of acquired data. The XANI workflow utilizes deep learning algorithms to detect patterns, classify conditions, and assist in diagnosis.
How XANI Works
The XANI workflow starts with the upload of x-ray images. The images are then standardized and evaluated for key findings using AI algorithms. The AI algorithms use computer vision and deep learning to detect patterns, classify conditions, and assist in diagnosis. The XANI workflow has been accelerated using NVIDIA technology, including the GB200 Grace Blackwell Superchip, to process and analyze large amounts of data quickly and accurately.
💡 Accelerating XANI
The XANI workflow has been accelerated 43x on a single GPU on a GB200 Grace Blackwell Superchip and 1,000x on 64 GPUs.
Benefits of XANI
The XANI workflow has several benefits, including faster and more accurate analysis of x-ray images. The XANI workflow can process and analyze large amounts of data quickly and accurately, enabling researchers to accelerate their research. The XANI workflow also enables researchers to track structural and electron dynamics in novel systems, including fusion materials, semiconducters, batteries, and catalysis.
43x
acceleration on single GPU
1,000x
acceleration on 64 GPUs
Future of XANI
The XANI workflow has the potential to revolutionize the field of nanoscale imaging. The XANI workflow can be used to accelerate research in various fields, including materials science, biology, and chemistry. The XANI workflow can also be used to develop new technologies, including more efficient solar cells and more effective medical treatments.
XANI vs Traditional Methods
XANI vs Traditional Methods
| Component | Open / This Approach | Proprietary Alternative |
|---|---|---|
| Computational Time | Less than 4 hours | 9 months |
| Accuracy | High | Lower |
🔑 Key Takeaway
The XANI workflow has the potential to revolutionize the field of nanoscale imaging by accelerating research and developing new technologies. The XANI workflow can process and analyze large amounts of data quickly and accurately, enabling researchers to accelerate their research.
Key Links