I can't find any performance benchmark in the home page.Any links?Thanks.
2014-03-31 2:01 GMT+08:00 Michał Marczyk :
> Hi,
>
> I am pleased to announce the 0.0.11 release of core.rrb-vector, a
> Clojure Contrib library extending the Clojure vector API with
> logarithmic-time concatenation and s
Thanks Andy!
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Hi,
I am pleased to announce the 0.0.11 release of core.rrb-vector, a
Clojure Contrib library extending the Clojure vector API with
logarithmic-time concatenation and slicing:
https://github.com/clojure/core.rrb-vector
[org.clojure/core.rrb-vector "0.0.11"]
org.clojure
core.rrb-v
In clarifying and correcting my example I found the issue. I was storing a
lambda deep inside some data structure and later updating the lambda code
to catch exceptions but an effectively cached lambda in my session wasn't
updated to the changed one (the evils of state..). A fresh session where
doh. that's a badly translated example by me. I'll have another go at
translating the actual code that isn't completely broken like attempt 1.
On Sunday, March 30, 2014 2:24:38 PM UTC+1, Michał Marczyk wrote:
>
> The problem is that inner-lazy is a method of AProto which is
> implemented for ARe
The problem is that inner-lazy is a method of AProto which is
implemented for ARecord, but actually called (in trigger-fn) on a
vector of two ARecords. The exception thrown is an
IllegalArgumentException complaining about the missing method.
inner-lazy2 works, because it's just a regular function.
I'm trying to work out how to catch exceptions close to source in some code
with structure similar to this:
https://www.refheap.com/68851
A doall on line 13 doesn't change the outcome.
So not involving records and protocol a similar structure does what I
expect it to do, but with them I seem un
Memory access patterns make a huge a difference to memory throughput. I've
explored this in some detail in the following blog.
http://mechanical-sympathy.blogspot.co.uk/2012/08/memory-access-patterns-are-important.html
On Sunday, 30 March 2014 06:40:24 UTC+1, Andy C wrote:
>
>
> Hi,
>
> So this
On 30/03/14 07:40, Andy C wrote:
Here are results where numbers are normalized gains.
++---++
| # of processes | random | linear|
++---++
|1 | 1.00| 1.00 |
++---+