Floating point exception (core dumped) ？ about ppl.nn HOT 4 OPEN

如果关掉这个选项 -DPPLNN_ENABLE_CUDA_JIT=OFF，就不会有上面的错误。但是不打开这个选项，性能是不是也会有所下降，我测试了benchmark，各个模型的性能都不如tensorrt好

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我也遇到类似的问题，还不知道如何解决。

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我也遇到类似的问题，还不知道如何解决。
Hello, I have no RTX3090 to be tested. And I tested mnasnet0_5.onnx on T4 and A100 with cuda=11.2 and JIT=ON, but these all works fine. I suggest you to substitute conv_jit.cc:Line599~600 with:
int cta_num_limit_by_regs = (regs_per_cta == 0) ? cta_num_limit_by_thds : max_regs_per_sm / regs_per_cta; int cta_num_limit_by_smem = (smem_per_cta == 0) ? cta_num_limit_by_thds : max_smem_per_sm / smem_per_cta;
and then test again. Please report the result on RTX3090, thx.

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我也遇到类似的问题，还不知道如何解决。
Hello, I have no RTX3090 to be tested. And I tested mnasnet0_5.onnx on T4 and A100 with cuda=11.2 and JIT=ON, but these all works fine. I suggest you to substitute conv_jit.cc:Line599~600 with:
int cta_num_limit_by_regs = (regs_per_cta == 0) ? cta_num_limit_by_thds : max_regs_per_sm / regs_per_cta; int cta_num_limit_by_smem = (smem_per_cta == 0) ? cta_num_limit_by_thds : max_smem_per_sm / smem_per_cta;
and then test again. Please report the result on RTX3090, thx.

Hi,
I tried your suggestion and modified the code, but the problem still persists on 3090. In addition, there is no problem in my multiple tests on the T4 and Jetson series.

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