Sparsity on DLA limitations

Autonomous Machines Jetson & Embedded Systems Jetson AGX Orin
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1

Hello,

I would like to get more explanation about what do you mean by this DLA sparsity limitations here :

  • Only convolutions whose quantized INT8 weights are at most 256K can benefit from SS–in practice, the limitation may be more restrictive.
  • Only convolutions with K % 64 in {0, 1, 2, 4, 8, 16, 32}, where K is the number of kernels (corresponding to the number of output channels), can benefit from SS in this release.

Thank you
Harry

5

Dear @Harry-S,
Are you asking what caused these limitations?

6

Hello @SivaRamaKrishnaNV ,

I would like to get a clarification of what is the meanins of these limitations.
for example what does quantized INT8 weights are at most 256K means?

Thank you

7

I got the same question. For 2d conv, does it mean I can only use INT8 weights with sparsity 2:4? I would be grateful if you can provide some examples.