vulkan: use flops instead of weight tensor size for submission heuristic

[0cc4m]

Overview

My guess for the long-running issues with DeviceLost errors on AMD and Intel due to submission timeouts is that we currently only treat matmuls as special in the submission batching logic, by taking the combined size of their weight matrices into account. But Flash Attention and convolutions are also very heavy operations that should be considered here. This doesn't work in the same way, so in this PR I'm trying to use FLOPs instead of weight matrix size weights for submission estimation. That should be easier to expand to other operators that might come in in the future.

This also fixes a bug where previously uint64_t mul_mat_bytes_per_submit = std::min(uint64_t(100*1000*1000), ctx->last_total_mul_mat_bytes / 40u); would always submit each operator separately on the first run, because ctx->last_total_mul_mat_bytes would start out as 0, so always be smaller than 100 MiB.

I'm still trying to reproduce the DeviceLost error on one of my devices.

Requirements

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• AI usage disclosure: YES, Claude was used for assistance, code was reviewed and tested by me.