AI Computing Architecture
3 Processing Types
1. Sequential Processing
- Hardware: General CPU (Intel/ARM)
- Function: Control flow, I/O, scheduling, Data preparation
- Workload Share: Training 5%, Inference 5%
2. Parallel Stream Processing
- Hardware: CUDA core (Stream process)
- Function: FP32/FP16 Vector/Scalar, memory management
- Workload Share: Training 10%, Inference 30%
3. Matrix Processing
- Hardware: Tensor core (Matrix core)
- Function: Mixed-precision (FP8/FP16) MMA, Sparse matrix operations
- Workload Share: Training 85%+, Inference 65%+
Key Insight
The majority of AI workloads are concentrated in matrix processing because matrix multiplication is the core operation in deep learning. Tensor cores are the key component for AI performance improvement.
With Claude
Lechuck Park 