[SUNIX] All-New AI Accelerator Card with High Efficiency & Energy-Saving Features!
Edge AI image recognition finds extensive applications in diverse industries. It improves quality control in manufacturing, aids in medical diagnosis and patient care, monitors crops in agriculture, optimizes inventory management in retail, conducts traffic analysis in transportation, and enhances urban planning in smart cities. Its versatile applications revolutionize the workflow of AI inference, boosting efficiency, and providing valuable support for decision-making.
Upgrade PC into AI computing
SUNIX introduces a PCIe AI acceleration card that seamlessly integrates AI processors into edge computers, providing developers with an easily deployable solution. This solution aims to reduce the CPU workload by offering higher processing performance and lower power consumption. It excels in achieving low-latency deep learning inference, providing cost-effective results for edge AI computing, especially in handling demanding computer vision applications. The robust software package ensures plug-and-play support and allows upgrading traditional computers such as NVRs, Edge AI box, industrial computers, and robots. This equips them to perform image analysis, traffic management, access control, and other intensive image analysis tasks, meeting the demands of specific missions in edge AI applications.
SUNIX AI accelerator performance comparison (Yolov5m)
With the "Yolov5m" image recognition model, SUNIX's accelerator card outperforms Nvidia A4000 by processing frames per second (FPS) 1.3 times faster. AIEH2000's energy efficiency is notable, computing 27 frames per watt (FPS/W) compared to Nvidia A4000's 3 FPS/W, resulting in over 11 times the energy savings. This highlights SUNIX's AI accelerator card as not only high-performing but also cost-effective, especially in widespread AI edge computing applications.
SUNIX AI visual recognition case
Product family
Since the launch of the world's first single-chip serial card in 1995, SUNIX has maintained a leading position in business communications. Leveraging a top-tier and experienced R&D team, we have extended our reach into the realm of Artificial Intelligence of Things (AIoT). Collaborating with partners worldwide, driving innovation towards an intelligent future.
[SUNIX] All-New AI Accelerator Card with High Efficiency & Energy-Saving Features!
Edge AI image recognition finds extensive applications in diverse industries. It improves quality control in manufacturing, aids in medical diagnosis and patient care, monitors crops in agriculture, optimizes inventory management in retail, conducts traffic analysis in transportation, and enhances urban planning in smart cities. Its versatile applications revolutionize the workflow of AI inference, boosting efficiency, and providing valuable support for decision-making.
Upgrade PC into AI computing
SUNIX introduces a PCIe AI acceleration card that seamlessly integrates AI processors into edge computers, providing developers with an easily deployable solution. This solution aims to reduce the CPU workload by offering higher processing performance and lower power consumption. It excels in achieving low-latency deep learning inference, providing cost-effective results for edge AI computing, especially in handling demanding computer vision applications. The robust software package ensures plug-and-play support and allows upgrading traditional computers such as NVRs, Edge AI box, industrial computers, and robots. This equips them to perform image analysis, traffic management, access control, and other intensive image analysis tasks, meeting the demands of specific missions in edge AI applications.
SUNIX AI accelerator performance comparison (Yolov5m)
With the "Yolov5m" image recognition model, SUNIX's accelerator card outperforms Nvidia A4000 by processing frames per second (FPS) 1.3 times faster. AIEH2000's energy efficiency is notable, computing 27 frames per watt (FPS/W) compared to Nvidia A4000's 3 FPS/W, resulting in over 11 times the energy savings. This highlights SUNIX's AI accelerator card as not only high-performing but also cost-effective, especially in widespread AI edge computing applications.
SUNIX AI visual recognition case
Product family
Since the launch of the world's first single-chip serial card in 1995, SUNIX has maintained a leading position in business communications. Leveraging a top-tier and experienced R&D team, we have extended our reach into the realm of Artificial Intelligence of Things (AIoT). Collaborating with partners worldwide, driving innovation towards an intelligent future.
[SUNIX] All-New AI Accelerator Card with High Efficiency & Energy-Saving Features!
Edge AI image recognition finds extensive applications in diverse industries. It improves quality control in manufacturing, aids in medical diagnosis and patient care, monitors crops in agriculture, optimizes inventory management in retail, conducts traffic analysis in transportation, and enhances urban planning in smart cities. Its versatile applications revolutionize the workflow of AI inference, boosting efficiency, and providing valuable support for decision-making.
Upgrade PC into AI computing
SUNIX introduces a PCIe AI acceleration card that seamlessly integrates AI processors into edge computers, providing developers with an easily deployable solution. This solution aims to reduce the CPU workload by offering higher processing performance and lower power consumption. It excels in achieving low-latency deep learning inference, providing cost-effective results for edge AI computing, especially in handling demanding computer vision applications. The robust software package ensures plug-and-play support and allows upgrading traditional computers such as NVRs, Edge AI box, industrial computers, and robots. This equips them to perform image analysis, traffic management, access control, and other intensive image analysis tasks, meeting the demands of specific missions in edge AI applications.
SUNIX AI accelerator performance comparison (Yolov5m)
With the "Yolov5m" image recognition model, SUNIX's accelerator card outperforms Nvidia A4000 by processing frames per second (FPS) 1.3 times faster. AIEH2000's energy efficiency is notable, computing 27 frames per watt (FPS/W) compared to Nvidia A4000's 3 FPS/W, resulting in over 11 times the energy savings. This highlights SUNIX's AI accelerator card as not only high-performing but also cost-effective, especially in widespread AI edge computing applications.
SUNIX AI visual recognition case
Product family
Since the launch of the world's first single-chip serial card in 1995, SUNIX has maintained a leading position in business communications. Leveraging a top-tier and experienced R&D team, we have extended our reach into the realm of Artificial Intelligence of Things (AIoT). Collaborating with partners worldwide, driving innovation towards an intelligent future.
[SUNIX] All-New AI Accelerator Card with High Efficiency & Energy-Saving Features!
Edge AI image recognition finds extensive applications in diverse industries. It improves quality control in manufacturing, aids in medical diagnosis and patient care, monitors crops in agriculture, optimizes inventory management in retail, conducts traffic analysis in transportation, and enhances urban planning in smart cities. Its versatile applications revolutionize the workflow of AI inference, boosting efficiency, and providing valuable support for decision-making.
Upgrade PC into AI computing
SUNIX introduces a PCIe AI acceleration card that seamlessly integrates AI processors into edge computers, providing developers with an easily deployable solution. This solution aims to reduce the CPU workload by offering higher processing performance and lower power consumption. It excels in achieving low-latency deep learning inference, providing cost-effective results for edge AI computing, especially in handling demanding computer vision applications. The robust software package ensures plug-and-play support and allows upgrading traditional computers such as NVRs, Edge AI box, industrial computers, and robots. This equips them to perform image analysis, traffic management, access control, and other intensive image analysis tasks, meeting the demands of specific missions in edge AI applications.
SUNIX AI accelerator performance comparison (Yolov5m)
With the "Yolov5m" image recognition model, SUNIX's accelerator card outperforms Nvidia A4000 by processing frames per second (FPS) 1.3 times faster. AIEH2000's energy efficiency is notable, computing 27 frames per watt (FPS/W) compared to Nvidia A4000's 3 FPS/W, resulting in over 11 times the energy savings. This highlights SUNIX's AI accelerator card as not only high-performing but also cost-effective, especially in widespread AI edge computing applications.
SUNIX AI visual recognition case
Product family
