[Graph][Benchmark] Update benchmark function

[Aalanli]

The old benchmarking function did not clear the l2 cache, so repeated runs are biased.
This is especially prevalent in tuning for parallel-k parts, which always selects k_parts=1 due to l2 cache hits, even when it is not the fastest implementation.

[yaoyaoding]

Hi Allan,

The PR looks good to me. But before merging, it is better to have some demos on the improvement of the accuracy on the selection of parallel k when we clear the L2 cache.

[Aalanli]

After some further investigation, it appears that the clearing of the l2 cache is not the greatest contributor, but the usage of torch.cuda.Event, which I assume to be more accurate than time.time().
Here is my benchmarking script for reference: https://gist.github.com/Aalanli/b81d1a751a78ea72b491d872aa993f9e

[Aalanli]

orig-latency is the original benchmark function
new-latency is the benchmark function used by this pr
orig-latency-with-event is a benchmark function that uses torch.cuda.Event, but does not clear l2 cache.

[Aalanli]

I just removed the torch dependencies.