[GitHub] [incubator-tvm] tqchen commented on pull request #5914: [clflush] Enable x86 cpu cache flush

[GitBox <gi...@apache.org>]

tqchen commented on pull request #5914:
URL: https://github.com/apache/incubator-tvm/pull/5914#issuecomment-648903111


   I like the overall util for cache flushing, however, it would be great to discuss the interface of cache eviction. In terms the API choices:
   
   - While it is understandable that we could like to include first argument(activation) and flush the rest of the argument, it is still a very specific setup(ideally it might be better to make it configurable).
   - Right now things are configured through env variable, is it the best way to configure API?
   - The current logic does not check for other context(besides CPU), and will results un determined behavior when we use OpenCL or CUDA(because the opaque data ptr does not corresponds to a CPU addresss), it might also cause problem when the function is not an DLTensor
   
   Here are a few alternative API choices for configuring the cache flushing behavior.
   
   ### A0: Fold cache flushing factor into time_evaluator
   
   ```python
   mod = load_module()
   # flush cpu cache of args 1
   f = mod.time_evaluator("myfunc", repeat=10, cache_flush_cpu_args_begin=1)
   ```
   
   
   ### A1: Decoupled Composite style
   ```python
   mod = load_module()
   # cache flush packed is a packed func that performs the cpu cache flush
   cache_flush_packed = remote.get_function("cpu_cache_flush")(args=begin=1)
   # fprepare is a callback that will be called before the evaluation, it takes in args as arguments. 
   f = mod.time_evaluator("myfunc", repeat=10, fprepare=cache_flush_packed)
   ```
   
   


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