this post was submitted on 23 Nov 2023
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Surely it cant be due to be AI performance?
The 7900xt is 103 tlops of fp16, 7900xtx is 122.
the 4070 is at 117 of fp16 (234 using sparsity) on a smaller chip and thats not banned.
The law only restricted raw FLOPs, so it has to be that. But the law has a chiplet subclause so it might be there’s some interaction there that pushes the AMD gpus over the edge.
the 4070 ti at 294mm2 (full ad104) with 160 Tflops of Fp16
The 7900xtx GCD is 300 mm2 (Full Navi31 GCD only) with 122 tflops of Fp16
Doubt its that.
Where there might be reasons is that RDNA doesnt hasve AI cores. The tasks are accelerated on the shader cores.Hence the term AI Accelarators. Now assumming nvidia cards ignore the tensor cores.
The 4090 can do only 82.6 Tflop of FP16 (Non-Tensor).
The 7900xtx would still retain its 122 tflops of FP16. making it faster in Fp16 performance.
doesn't RDNA3 have WAVA MMA or Wave Matrix Multiply Accumulate which is their AI cores?
It has the instruction sets in the compute units
They are called AI accelerators for that reason.
Not Ai cores.
The actual Matrix "Cores" , i.e. dedicated silicon, are on the instinct series
No. Tensor cores have seperate specialised matrix ALUs, AMD's WMMA are instructions on existing shader ALUs.
Tensor cores can process AI tasks in parallel to CUDA cores, RDNA3 can't do both on the same CU.