Estimate Complexity

To estimate the total number of FLOPs required to train GPT-3, we use the following reasoning:

1. Model Parameters (P):
   GPT-3 has 175 billion parameters ((P = 175 imes 10^9)).

2. Training Tokens (N):
   GPT-3 was trained on approximately 300 billion tokens ((N = 300 imes 10^9)).

3. FLOPs per Token:

   • A forward pass requires ~(2P) FLOPs per token (each parameter involves a multiply-accumulate operation, which counts as 2 FLOPs).
   • A backward pass (for gradients) is roughly twice as expensive as the forward pass, requiring ~(4P) FLOPs per token.
   • Total FLOPs per token: (2P + 4P = 6P).

4. Total Training FLOPs:
   Multiply FLOPs per token by the total number of tokens:
   [ ext{FLOPs} = 6 imes P imes N = 6 imes 175 imes 10^9 imes 300 imes 10^9 = 3.15 imes 10^{23} , ext{FLOPs}. ]

Final Answer:
The total number of FLOPs required to train GPT-3 is approximately (3.1 imes 10^{23}) FLOPs.