Kayvon said that the ability for the user to customize scheduling policy makes GraphLab an "unclean" abstraction. Doesn't GraphLab also take care of scheduling if the user does not provide a policy, just like Lizst? I guess what I'm asking is why does having a clean abstraction matter if we know that whatever scheduling policy Lizst/GraphLab tries to come up (in some cases) will not be as good as the scheduling policies we put in place. Because like the slide says, this is common and necessary in designing efficient/fast algorithms.
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bstan
I don't think that Kayvon implied that a clean abstraction is necessarily better - he was probably just pointing out the differences. Having a clean abstraction allows the user to not have to (or, makes the user unable to) worry about implementation details. It would be 'cleaner' and more representative of what is trying to be accomplished. On the other hand, an unclean abstraction allows users more flexibility in optimization.
Kayvon said that the ability for the user to customize scheduling policy makes GraphLab an "unclean" abstraction. Doesn't GraphLab also take care of scheduling if the user does not provide a policy, just like Lizst? I guess what I'm asking is why does having a clean abstraction matter if we know that whatever scheduling policy Lizst/GraphLab tries to come up (in some cases) will not be as good as the scheduling policies we put in place. Because like the slide says, this is common and necessary in designing efficient/fast algorithms.
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I don't think that Kayvon implied that a clean abstraction is necessarily better - he was probably just pointing out the differences. Having a clean abstraction allows the user to not have to (or, makes the user unable to) worry about implementation details. It would be 'cleaner' and more representative of what is trying to be accomplished. On the other hand, an unclean abstraction allows users more flexibility in optimization.
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