[...]
I am curious to see how this compares to simple for-loops which I can
imagine help the JIT compiler to do loop unrolling and to make use of
instruction-level parallelism.
Otmar,
Just read another article that evaluated some of Angelika Langers results.
http://blog.codefx.org/java/stream-p
On 01/03/2016 02:06 AM, Otmar Ertl wrote:
Am 03.01.2016 7:49 vorm. schrieb "Ole Ersoy" :
Hi,
I ran another test using a single parallel loop for array based matrix
vector multiplication. Throughput almost tripled (Test pasted at bottom):
# Run complete. Total time: 00:13:24
Benchmark
Am 03.01.2016 7:49 vorm. schrieb "Ole Ersoy" :
>
> Hi,
>
> I ran another test using a single parallel loop for array based matrix
vector multiplication. Throughput almost tripled (Test pasted at bottom):
>
> # Run complete. Total time: 00:13:24
>
>
> Benchmark
Hi,
I ran another test using a single parallel loop for array based matrix vector
multiplication. Throughput almost tripled (Test pasted at bottom):
# Run complete. Total time: 00:13:24
Benchmark Mode Cnt Score Error Units
MultiplyBenchmark.parallelMulti
Hi Otmar,
On 01/02/2016 10:33 AM, Otmar Ertl wrote:
On Sat, Jan 2, 2016 at 4:38 AM, Ole Ersoy wrote:
Hi,
Hope ya'll are having an awesome new year!
Some matrix operations, like createRealIdentityMatrix can be turned into one
liners like this:
IntStream.range(0, dimension).forEach(i
On Sat, Jan 2, 2016 at 4:38 AM, Ole Ersoy wrote:
> Hi,
>
> Hope ya'll are having an awesome new year!
>
> Some matrix operations, like createRealIdentityMatrix can be turned into one
> liners like this:
>
>IntStream.range(0, dimension).forEach(i -> m.setEntry(i, i, 1.0));
>
> And can be pe
Hi,
Hope ya'll are having an awesome new year!
Some matrix operations, like createRealIdentityMatrix can be turned into one
liners like this:
IntStream.range(0, dimension).forEach(i -> m.setEntry(i, i, 1.0));
And can be performed in parallel like this:
IntStream.range(0, dimens
