The tests are still running. I want to make sure they all pass before
another round of benchmarks. :)


On Mon, Apr 22, 2013 at 8:00 PM, Robin Anil <[email protected]> wrote:

> Can you update/create a spreadsheet of where you are right now v/s trunk
> On Apr 22, 2013 11:51 AM, "Dan Filimon" <[email protected]>
> wrote:
>
>> In fact the issue I was referring to turns out to be because the very
>> fast case was in fact wrong.
>> When merging two sparse vectors I wasn't updating the number of mappings
>> in the result.
>>
>> Performance is now better for the more "tuned" vectors.
>> I have noticed some random regressions with dense vectors ... this is
>> pretty odd. :/
>>
>> Anyway, can you give me some insight into:
>> - what exactly the numbers in the spreadsheet mean?
>> - what is the "Cluster" score for some benchmarks? There don't seem to be
>> explicit calls to any cluster vectors.
>>
>> Thanks!
>>
>>
>>
>> On Mon, Apr 22, 2013 at 5:24 PM, Robin Anil <[email protected]> wrote:
>>
>>> Yes every time you replace primitive call you are at the mercy of jit to
>>> inline the method. Choose primitive wherever possible to reduce variability
>>>  On Apr 22, 2013 7:15 AM, "Dan Filimon" <[email protected]>
>>> wrote:
>>>
>>>> Thanks!
>>>>
>>>> So, I'm running more benchmark and it's a mixed bag. There are
>>>> regressions and gains, but what surprises me the most is that after
>>>> replacing every "primitive" call with calls to assign/aggregate, the
>>>> clustering behaves much worse.
>>>>
>>>> As in, dozens (literally) of times worse. I'm surprised it's so bad,
>>>> yet doesn't show in the benchmarks.
>>>> Any ideas why this might be, or what I should look into?
>>>>
>>>>
>>>> On Sat, Apr 20, 2013 at 9:14 PM, Robin Anil <[email protected]>wrote:
>>>>
>>>>>
>>>>> https://docs.google.com/spreadsheet/ccc?key=0AhewTD_ZgznddGFQbWJCQTZXSnFULUYzdURfWDRJQlE#gid=2
>>>>>
>>>>> Here you go. There are some regressions and some improvements. One of
>>>>> the major reasons I think is replacing inline math with foo.apply(). JVM
>>>>> might not have optimized it yet. You might be better off but just adding 
>>>>> an
>>>>> AggregateBenchmark and working on it for your functions before replacing
>>>>> entire AbstractVector methods.
>>>>>
>>>>
>>>>
>>

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