[webgpu] update perf test

[haoyunfeix]

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[haoyunfeix]

@qjia7 @xhcao @gyagp @axinging PTAL

[gyagp]

LGTM

[xhcao]

Another comment is that why there are some many variables and all these ones are defined in functions. Could we define some of them in the global scope or wrap some variables together to reduce some definations.

[xhcao]

In tf.profile,

1. I think we mainly profile const result = tf.matMul(tensors[i].tensorA, tensors[i].tensorB), would including warmup model and warmup gpu parts influence the correctness?
2. Why we still need to execute tf.matMul(tensorsWarmUp.tensorA, tensorsWarmUp.tensorB) in the 3rd for-loop, I think the cost time of it may be larger than tf.matMul(tensors[i].tensorA, tensors[i].tensorB), which is the real main workload.
3. How to make sure that all matMul commands are executed one by one? I think they may be executed synchronously here?

[haoyunfeix]

1. Yes, warmup model is for the first run of each matmul shape(costing large shader generate and buffer creating time ... which leads to a significant deviation from the average value) and warmup gpu is to make every shape of inputs could be measured in the same frequency.
2. The idea to insert a large warmup tensor between each main workload is also to keep high frequency, the real main workload will pull down the frequency if they execute together, please see below pictures:
   with: keep frequency at almost 1200M
   
   without: Visible jitter, break the measurement accurate (only happens on WebGPU)
   
3. You're right, serial execution would be considered in another PR.

[xhcao]

Why we wrap the dimAOuter | dimInner | dimBOuter into a string here, and should encode and decode the string? Why not wrap this value into an array or a structure?

[haoyunfeix]

Each row has a rerun button to help rerun a single case for double check. And this button catches shape infos(e.g. [16, 512, 16]) from HTML element, which value must be a string. So here I used the raw data what I get from the page.

[qjia7]

LGTM, thanks.

As we synced offline, we can do more refactor based on it.