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<title>symlbm_playground/template, branch ink</title>
<subtitle>Tinkering with LBM, OpenCL and SymPy-based code generation</subtitle>
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<entry>
<title>Cleanup</title>
<updated>2019-09-11T17:12:29+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-09-11T17:12:29+00:00</published>
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<pre>
</pre>
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</entry>
<entry>
<title>Add a fun little fake bonfire _simulation_</title>
<updated>2019-09-06T20:29:05+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-09-06T20:29:05+00:00</published>
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…using appropriately colored aging particles
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<pre>
…using appropriately colored aging particles
</pre>
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</content>
</entry>
<entry>
<title>Reset stuck particles to starting position</title>
<updated>2019-09-04T20:52:38+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-09-04T20:52:38+00:00</published>
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<pre>
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</content>
</entry>
<entry>
<title>Prototype "ink" particles visualization</title>
<updated>2019-09-01T21:06:10+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-09-01T21:06:10+00:00</published>
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<pre>
</pre>
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</entry>
<entry>
<title>Dampen channel inflow</title>
<updated>2019-07-25T18:59:06+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-07-25T18:59:06+00:00</published>
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</entry>
<entry>
<title>Implement layout and memory padding</title>
<updated>2019-06-29T21:45:47+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-06-29T21:45:47+00:00</published>
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<content type='text'>
There are at least two distinct areas where padding can be beneficial on a GPU:

1. Padding the global thread sizes to support specific thread layouts
   e.g. (32,1) layouts require the global lattice width to be a multiple of 32
2. Padding the memory layout at the lowest level to align memory accesses
   i.e. some GPUs read memory in 128 Byte chunks and as such it is beneficial if
   the operations are aligned accordingly

For lattice and thread layout sizes that are exponents of two these two padding
areas are equivalent. However when one operates on e.g. a (300,300) lattice using
a (30,1) layout, padding to 128 bytes yields a performance improvement of about
10 MLUPS on a K2200.

Note that I am getting quite unsatisfied with how the Lattice class and
its suroundings continue to accumulate parameters. The naming distinction
between Geometry, Grid, Memory and Lattice is also not very intuitive.
</content>
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<pre>
There are at least two distinct areas where padding can be beneficial on a GPU:

1. Padding the global thread sizes to support specific thread layouts
   e.g. (32,1) layouts require the global lattice width to be a multiple of 32
2. Padding the memory layout at the lowest level to align memory accesses
   i.e. some GPUs read memory in 128 Byte chunks and as such it is beneficial if
   the operations are aligned accordingly

For lattice and thread layout sizes that are exponents of two these two padding
areas are equivalent. However when one operates on e.g. a (300,300) lattice using
a (30,1) layout, padding to 128 bytes yields a performance improvement of about
10 MLUPS on a K2200.

Note that I am getting quite unsatisfied with how the Lattice class and
its suroundings continue to accumulate parameters. The naming distinction
between Geometry, Grid, Memory and Lattice is also not very intuitive.
</pre>
</div>
</content>
</entry>
<entry>
<title>Add platform, precision and thread layout parameters</title>
<updated>2019-06-22T12:44:50+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-06-22T12:44:50+00:00</published>
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</entry>
<entry>
<title>Gather interop moments in a more generic manner</title>
<updated>2019-06-21T18:41:11+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-06-21T18:41:11+00:00</published>
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i.e. return unshifted moments in a implicitly ordered float4 array.
Cell positions are reconstructed by a vertex shaded analogously to
how it is done in compustream.
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i.e. return unshifted moments in a implicitly ordered float4 array.
Cell positions are reconstructed by a vertex shaded analogously to
how it is done in compustream.
</pre>
</div>
</content>
</entry>
<entry>
<title>Prototype OpenGL interoperation</title>
<updated>2019-06-20T13:43:58+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-06-20T13:43:58+00:00</published>
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<pre>
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</content>
</entry>
<entry>
<title>Extract population offset</title>
<updated>2019-06-17T18:11:43+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-06-17T18:11:43+00:00</published>
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<pre>
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</content>
</entry>
<entry>
<title>Declutter gid and offset calculation</title>
<updated>2019-06-16T11:51:35+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-06-16T11:51:35+00:00</published>
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<pre>
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</entry>
<entry>
<title>Add support for generating a D3Q19 kernel</title>
<updated>2019-06-15T18:54:56+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-06-15T18:45:27+00:00</published>
<link rel='alternate' type='text/html' href='https://code.kummerlaender.eu/symlbm_playground/commit/?id=d71faec93ec0a55c46810e0d178b2803ee89130c'/>
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<content type='text'>
Note how this basically required no changes besides generalizing cell indexing
and adding the symbolic formulation of a D3Q19 BGK collision step.

Increasing the neighborhood communication from 9 to 19 cells leads to a
significant performance "regression": The 3D kernel yields ~ 360 MLUPS
compared to the 2D version's ~ 820 MLUPS.
</content>
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<pre>
Note how this basically required no changes besides generalizing cell indexing
and adding the symbolic formulation of a D3Q19 BGK collision step.

Increasing the neighborhood communication from 9 to 19 cells leads to a
significant performance "regression": The 3D kernel yields ~ 360 MLUPS
compared to the 2D version's ~ 820 MLUPS.
</pre>
</div>
</content>
</entry>
<entry>
<title>Consistently name population buffers</title>
<updated>2019-06-15T12:18:32+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-06-15T12:18:32+00:00</published>
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</entry>
<entry>
<title>Extract geometry information</title>
<updated>2019-06-14T20:44:44+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-06-14T20:44:44+00:00</published>
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</entry>
<entry>
<title>Further the separation between descriptor and lattice</title>
<updated>2019-06-13T19:55:18+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-06-13T19:45:49+00:00</published>
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</entry>
<entry>
<title>Tidy up symbolic kernel generation</title>
<updated>2019-06-13T19:19:49+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-06-13T19:19:49+00:00</published>
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</entry>
<entry>
<title>Add kernel customization point for velocity boundaries</title>
<updated>2019-06-13T16:08:14+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-06-13T16:08:14+00:00</published>
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</entry>
<entry>
<title>Make it easier to exchange initial equilibration logic</title>
<updated>2019-06-12T20:20:51+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-06-12T20:20:51+00:00</published>
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<entry>
<title>Move kernel template into separate file</title>
<updated>2019-06-12T18:25:38+00:00</updated>
<author>
<name>Adrian Kummerlaender</name>
</author>
<published>2019-06-12T18:25:38+00:00</published>
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