For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/06/deepxs-new-m1-npu-delivers-flexibility-accuracy-efficiency-and-performance-a-presentation-from-deepx/ Jay Kim, Executive Vice President of DEEPX, presents the “DEEPX’s New M1 NPU Delivers Flexibility, Accuracy, Efficiency and Performance” tutorial at the May 2023 Embedded Vision Summit. For a growing range of applications, deploying AI in the real world means running various models at the edge. Fortunately, powerful edge processors are increasingly capable of handling demanding AI workloads. But performance alone is not sufficient. To meet the needs of real-world applications, edge AI processors must also deliver flexibility, accuracy and efficiency. In this talk, Kim presents DEEPX’s new M1 NPU. He explains how its unique architecture provides exceptional flexibility, enabling it to handle new DNN models and layer types with ease. Kim also shows how his company’s unique hardware/software co-design approach enables the M1 to deliver high performance with extreme cost- and energy-efficiency. And, finally, he shows how—despite its extreme efficiency—the new architecture achieves outstanding accuracy, comparable to that of GPUs.

1. DEEPX’s New M1 NPU Delivers
Flexibility, Accuracy, Efficiency
and Performance
Jay Kim
Executive Vice President
DEEPX

2. Disruptive Innovation “IT’S REAL”
2
© 2023 DEEPX
DX-M1: 133 FPS (Yolov7)
mAP: 50.9
00
V100: 229 FPS (Yolov7)
mAP: 51.0
Batch Size =1 Batch Size =1

3. DEEPX’s Key Differentiators
© 2023 DEEPX 3

4. DEEPX’s Key Differentiators – 1. Flexibility
4
© 2023 DEEPX
✓ Latest: Latest DNN algorithms (SOTA)
- EfficientNet , YoloX, YoloV7, PIDNet …
✓ Wide Range: Various kinds of algorithms
- Classification, object detection, segmentation,
pose estimation, anomaly detection …
✓ Complex Algorithms: Normally too complex for edge NPUs
- DeepX NPU can run PIDNet, SFA3D (Sensor Fusion)
→ Customers can use our NPU longer and wider.

5. Evidence #1: SOTA Support (Object Detection)
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© 2023 DEEPX

6. DEEPX’s Key Differentiators – 2. Accuracy
✓ Use int 8-bit instead of 32-bit floating point operations
- Expect accuracy drop comparing to GPU
✓ Almost the same accuracy as a GPU can get
- Normally same or less than 1% accuracy drop expected
✓ Wow factor: Better accuracy than GPU in some cases
- YoloXs, MobileNetv1, ResNet50, EfficientNet-B0 and etc
→ Customers can get the most accurate result with our NPU.
© 2023 DEEPX 6

7. Evidence #2: AI Accuracy Comparison
DEEPX accuracy is better than FP32 & other latest NPUs
© 2023 DEEPX 7

8. DEEPX’s Key Differentiators – 3. Efficiency
✓ Popular power efficiency factor (TOPS/W) with Resnet50
- World top power efficiency: over 10 TOPS/W
✓ Prefer other efficiency factor (FPS/TOPS)
- Actual result with 1 TOPS
✓ Finally pursue the effective power efficiency such as FPS/W
- Actual result with 1 Watt
→ Customers can get the max performance with the lowest power.
© 2023 DEEPX 8

9. Extreme Case: Ultra Low Power NPU
CMOS IMAGE SENSOR
Intelligent CMOS Image Sensor
• Image Enhancement NPU (PoC)
• Face Recognition Function NPU (PoC)
✓ 1 mm X 1 mm @40 nm
✓ Lower than 10 mW & 10 fps
✓ Face recognition accuracy
Image Enhancement
© 2023 DEEPX 9

10. Important Factor for Commercial Success:
DXNN™ – DEEPX NPU SDK
❖ Beta version of DXNN has been released to customers.
© 2023 DEEPX 10

11. 11
© 2023 DEEPX
Customer
Success Story

12. Success Story: Actual Throughput (1st Wow)
Performance
X 10
COST
X 10
Efficiency
X 100
=
© 2023 DEEPX 12
MSRP: $699.00 MSRP: $70.00

13. Success Story: Accuracy (2nd Wow)
87.6%
41.8%
89%
41.9%
1.4%↑
0.1%↑
© 2023 DEEPX 13

14. Success Story:
© 2023 DEEPX 14

15. Success Story: BOM Cost Reduction (4th Wow)
© 2023 DEEPX 15

16. Summary
DEEPX NPU can:
1. Run more SOTA AI models.
2. Get the most accurate results.
3. Achieve the best power efficiency.
4. Provide a cost efficient solution (including BOM).
Please visit our demo booth and check!
Thank you !!

17. Company Info, Demo and Additional Talk
2023 Embedded Vision Summit
Additional Talks from DEEPX:
1. “Toward the Era of AI Everywhere”
(Lokwon Kim, May 24, 10:50 am)
2. “State-of-the-Art Model
Quantization and Optimization for
Efficient Edge AI”
(Hyunjin Kim, May 24, 12:00 pm)
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1. Demo Booth: #103
2. DEEPX Homepage
https://www.deepx.ai
3. LinkedIn & Youtube
© 2023 DEEPX