#fluidx3d — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #fluidx3d, aggregated by home.social.
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#FluidX3D #CFD v3.7 brings faster Q-criterion isosurface rendering with #OpenCL local memory optimization! 🖖🤠
https://github.com/ProjectPhysX/FluidX3D/releases/tag/v3.7Instead of 32 velocities for each #GPU thread, now an 8x8x8 workgroup loads & reuses 11x11x11 velocities in L1$, a 12x VRAM BW reduction.
Fascinating insight: Which thread loads which cell from VRAM to L1$, and which thread renders which grid cell within the workgroup, can be very different!
https://github.com/ProjectPhysX/FluidX3D/blob/master/src/kernel.cpp#L2827-L2956PS: plugged X-wing Gif in #GitHub preview 🖖😜
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#FluidX3D #CFD v3.7 brings faster Q-criterion isosurface rendering with #OpenCL local memory optimization! 🖖🤠
https://github.com/ProjectPhysX/FluidX3D/releases/tag/v3.7Instead of 32 velocities for each #GPU thread, now an 8x8x8 workgroup loads & reuses 11x11x11 velocities in L1$, a 12x VRAM BW reduction.
Fascinating insight: Which thread loads which cell from VRAM to L1$, and which thread renders which grid cell within the workgroup, can be very different!
https://github.com/ProjectPhysX/FluidX3D/blob/master/src/kernel.cpp#L2827-L2956PS: plugged X-wing Gif in #GitHub preview 🖖😜
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#FluidX3D #CFD v3.7 brings faster Q-criterion isosurface rendering with #OpenCL local memory optimization! 🖖🤠
https://github.com/ProjectPhysX/FluidX3D/releases/tag/v3.7Instead of 32 velocities for each #GPU thread, now an 8x8x8 workgroup loads & reuses 11x11x11 velocities in L1$, a 12x VRAM BW reduction.
Fascinating insight: Which thread loads which cell from VRAM to L1$, and which thread renders which grid cell within the workgroup, can be very different!
https://github.com/ProjectPhysX/FluidX3D/blob/master/src/kernel.cpp#L2827-L2956PS: plugged X-wing Gif in #GitHub preview 🖖😜
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#FluidX3D #CFD v3.7 brings faster Q-criterion isosurface rendering with #OpenCL local memory optimization! 🖖🤠
https://github.com/ProjectPhysX/FluidX3D/releases/tag/v3.7Instead of 32 velocities for each #GPU thread, now an 8x8x8 workgroup loads & reuses 11x11x11 velocities in L1$, a 12x VRAM BW reduction.
Fascinating insight: Which thread loads which cell from VRAM to L1$, and which thread renders which grid cell within the workgroup, can be very different!
https://github.com/ProjectPhysX/FluidX3D/blob/master/src/kernel.cpp#L2827-L2956PS: plugged X-wing Gif in #GitHub preview 🖖😜
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#FluidX3D #CFD v3.7 brings faster Q-criterion isosurface rendering with #OpenCL local memory optimization! 🖖🤠
https://github.com/ProjectPhysX/FluidX3D/releases/tag/v3.7Instead of 32 velocities for each #GPU thread, now an 8x8x8 workgroup loads & reuses 11x11x11 velocities in L1$, a 12x VRAM BW reduction.
Fascinating insight: Which thread loads which cell from VRAM to L1$, and which thread renders which grid cell within the workgroup, can be very different!
https://github.com/ProjectPhysX/FluidX3D/blob/master/src/kernel.cpp#L2827-L2956PS: plugged X-wing Gif in #GitHub preview 🖖😜
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Newest #IntelArc #GPU family member is here, the Panther Lake Arc B390... and it... purrs? 🖖 🥺 🐈⬛
My OpenCL-Benchmark on the B390 measures ~7.4 TFlops FP32 and ~120GB/s memory bandwidth. hw-smi also works with the B390.
#FluidX3D benchmarks here: https://github.com/ProjectPhysX/FluidX3D#single-gpucpu-benchmarks
And the #OpenCL infos:
- Arc B390: https://opencl.gpuinfo.org/displayreport.php?id=6718
- Core Ultra X7 358H: https://opencl.gpuinfo.org/displayreport.php?id=6717 -
Newest #IntelArc #GPU family member is here, the Panther Lake Arc B390... and it... purrs? 🖖 🥺 🐈⬛
My OpenCL-Benchmark on the B390 measures ~7.4 TFlops FP32 and ~120GB/s memory bandwidth. hw-smi also works with the B390.
#FluidX3D benchmarks here: https://github.com/ProjectPhysX/FluidX3D#single-gpucpu-benchmarks
And the #OpenCL infos:
- Arc B390: https://opencl.gpuinfo.org/displayreport.php?id=6718
- Core Ultra X7 358H: https://opencl.gpuinfo.org/displayreport.php?id=6717 -
Newest #IntelArc #GPU family member is here, the Panther Lake Arc B390... and it... purrs? 🖖 🥺 🐈⬛
My OpenCL-Benchmark on the B390 measures ~7.4 TFlops FP32 and ~120GB/s memory bandwidth. hw-smi also works with the B390.
#FluidX3D benchmarks here: https://github.com/ProjectPhysX/FluidX3D#single-gpucpu-benchmarks
And the #OpenCL infos:
- Arc B390: https://opencl.gpuinfo.org/displayreport.php?id=6718
- Core Ultra X7 358H: https://opencl.gpuinfo.org/displayreport.php?id=6717 -
Newest #IntelArc #GPU family member is here, the Panther Lake Arc B390... and it... purrs? 🖖 🥺 🐈⬛
My OpenCL-Benchmark on the B390 measures ~7.4 TFlops FP32 and ~120GB/s memory bandwidth. hw-smi also works with the B390.
#FluidX3D benchmarks here: https://github.com/ProjectPhysX/FluidX3D#single-gpucpu-benchmarks
And the #OpenCL infos:
- Arc B390: https://opencl.gpuinfo.org/displayreport.php?id=6718
- Core Ultra X7 358H: https://opencl.gpuinfo.org/displayreport.php?id=6717 -
Newest #IntelArc #GPU family member is here, the Panther Lake Arc B390... and it... purrs? 🖖 🥺 🐈⬛
My OpenCL-Benchmark on the B390 measures ~7.4 TFlops FP32 and ~120GB/s memory bandwidth. hw-smi also works with the B390.
#FluidX3D benchmarks here: https://github.com/ProjectPhysX/FluidX3D#single-gpucpu-benchmarks
And the #OpenCL infos:
- Arc B390: https://opencl.gpuinfo.org/displayreport.php?id=6718
- Core Ultra X7 358H: https://opencl.gpuinfo.org/displayreport.php?id=6717 -
#FluidX3D #CFD has reached ⭐ 5000 Stargazers on #GitHub! 🖖🥳
Grid refinement update is still in development, I haven't forgotten... ⬜◻️◽▫️
https://github.com/ProjectPhysX/FluidX3D -
#FluidX3D #CFD has reached ⭐ 5000 Stargazers on #GitHub! 🖖🥳
Grid refinement update is still in development, I haven't forgotten... ⬜◻️◽▫️
https://github.com/ProjectPhysX/FluidX3D -
#FluidX3D #CFD has reached ⭐ 5000 Stargazers on #GitHub! 🖖🥳
Grid refinement update is still in development, I haven't forgotten... ⬜◻️◽▫️
https://github.com/ProjectPhysX/FluidX3D -
#FluidX3D #CFD has reached ⭐ 5000 Stargazers on #GitHub! 🖖🥳
Grid refinement update is still in development, I haven't forgotten... ⬜◻️◽▫️
https://github.com/ProjectPhysX/FluidX3D -
#FluidX3D #CFD has reached ⭐ 5000 Stargazers on #GitHub! 🖖🥳
Grid refinement update is still in development, I haven't forgotten... ⬜◻️◽▫️
https://github.com/ProjectPhysX/FluidX3D -
Finally Intel #GPU support on Linux too. Watch all the metrics go brrr in multi-GPU #FluidX3D #CFD workload! Will #opensource soon™️
Hardening against the myriads of broken counters in all those bugged APIs was a long shot. 🖖🫠
____________ | Windows | #Linux |
CPU / RAM | ✅️️WinAPI | ✅️️/proc |
#Nvidia GPU | ✅️️NVML | ✅️️NVML |
#Intel GPU | ✅IGCL | ✅SYSMAN |
#AMD GPU | ✅️️️️ADLX | ✅️️️️AMDSMI | -
Finally Intel #GPU support on Linux too. Watch all the metrics go brrr in multi-GPU #FluidX3D #CFD workload! Will #opensource soon™️
Hardening against the myriads of broken counters in all those bugged APIs was a long shot. 🖖🫠
____________ | Windows | #Linux |
CPU / RAM | ✅️️WinAPI | ✅️️/proc |
#Nvidia GPU | ✅️️NVML | ✅️️NVML |
#Intel GPU | ✅IGCL | ✅SYSMAN |
#AMD GPU | ✅️️️️ADLX | ✅️️️️AMDSMI | -
Finally Intel #GPU support on Linux too. Watch all the metrics go brrr in multi-GPU #FluidX3D #CFD workload! Will #opensource soon™️
Hardening against the myriads of broken counters in all those bugged APIs was a long shot. 🖖🫠
____________ | Windows | #Linux |
CPU / RAM | ✅️️WinAPI | ✅️️/proc |
#Nvidia GPU | ✅️️NVML | ✅️️NVML |
#Intel GPU | ✅IGCL | ✅SYSMAN |
#AMD GPU | ✅️️️️ADLX | ✅️️️️AMDSMI | -
Finally Intel #GPU support on Linux too. Watch all the metrics go brrr in multi-GPU #FluidX3D #CFD workload! Will #opensource soon™️
Hardening against the myriads of broken counters in all those bugged APIs was a long shot. 🖖🫠
____________ | Windows | #Linux |
CPU / RAM | ✅️️WinAPI | ✅️️/proc |
#Nvidia GPU | ✅️️NVML | ✅️️NVML |
#Intel GPU | ✅IGCL | ✅SYSMAN |
#AMD GPU | ✅️️️️ADLX | ✅️️️️AMDSMI | -
Finally Intel #GPU support on Linux too. Watch all the metrics go brrr in multi-GPU #FluidX3D #CFD workload! Will #opensource soon™️
Hardening against the myriads of broken counters in all those bugged APIs was a long shot. 🖖🫠
____________ | Windows | #Linux |
CPU / RAM | ✅️️WinAPI | ✅️️/proc |
#Nvidia GPU | ✅️️NVML | ✅️️NVML |
#Intel GPU | ✅IGCL | ✅SYSMAN |
#AMD GPU | ✅️️️️ADLX | ✅️️️️AMDSMI | -
#FluidX3D #CFD v3.6 is out! This release accumulates a number of small improvements over the last months. Most notably, better interactive graphics support on #macOS with XQuartz. Have fun! 🖖😎🌊🍏
https://github.com/ProjectPhysX/FluidX3D/releases/tag/v3.6 -
#FluidX3D #CFD v3.6 is out! This release accumulates a number of small improvements over the last months. Most notably, better interactive graphics support on #macOS with XQuartz. Have fun! 🖖😎🌊🍏
https://github.com/ProjectPhysX/FluidX3D/releases/tag/v3.6 -
#FluidX3D #CFD v3.6 is out! This release accumulates a number of small improvements over the last months. Most notably, better interactive graphics support on #macOS with XQuartz. Have fun! 🖖😎🌊🍏
https://github.com/ProjectPhysX/FluidX3D/releases/tag/v3.6 -
#FluidX3D #CFD v3.6 is out! This release accumulates a number of small improvements over the last months. Most notably, better interactive graphics support on #macOS with XQuartz. Have fun! 🖖😎🌊🍏
https://github.com/ProjectPhysX/FluidX3D/releases/tag/v3.6 -
#FluidX3D #CFD v3.6 is out! This release accumulates a number of small improvements over the last months. Most notably, better interactive graphics support on #macOS with XQuartz. Have fun! 🖖😎🌊🍏
https://github.com/ProjectPhysX/FluidX3D/releases/tag/v3.6 -
Finally, the bars for #Intel hardware in the #FluidX3D #mermaid gantt performance chart are BLUE, as nature intended it.
https://github.com/ProjectPhysX/FluidX3D?tab=readme-ov-file#single-gpucpu-benchmarks -
Finally, the bars for #Intel hardware in the #FluidX3D #mermaid gantt performance chart are BLUE, as nature intended it.
https://github.com/ProjectPhysX/FluidX3D?tab=readme-ov-file#single-gpucpu-benchmarks -
Finally, the bars for #Intel hardware in the #FluidX3D #mermaid gantt performance chart are BLUE, as nature intended it.
https://github.com/ProjectPhysX/FluidX3D?tab=readme-ov-file#single-gpucpu-benchmarks -
Finally, the bars for #Intel hardware in the #FluidX3D #mermaid gantt performance chart are BLUE, as nature intended it.
https://github.com/ProjectPhysX/FluidX3D?tab=readme-ov-file#single-gpucpu-benchmarks -
Finally, the bars for #Intel hardware in the #FluidX3D #mermaid gantt performance chart are BLUE, as nature intended it.
https://github.com/ProjectPhysX/FluidX3D?tab=readme-ov-file#single-gpucpu-benchmarks -
Some experimentation with ```mermaid ...``` charts in #GitHub #markdown. Turns out you can hack the formatting on the quadrantChart to turn it into an xy-scatter plot with individual point size/coloring/labeling.🖖🧐
First plot is datasheet memory bandwidth vs. FP32 TFlops/s, second plot is #FluidX3D performance vs. bandwidth, for lots of #GPU/#CPU hardware. -
Some experimentation with ```mermaid ...``` charts in #GitHub #markdown. Turns out you can hack the formatting on the quadrantChart to turn it into an xy-scatter plot with individual point size/coloring/labeling.🖖🧐
First plot is datasheet memory bandwidth vs. FP32 TFlops/s, second plot is #FluidX3D performance vs. bandwidth, for lots of #GPU/#CPU hardware. -
Some experimentation with ```mermaid ...``` charts in #GitHub #markdown. Turns out you can hack the formatting on the quadrantChart to turn it into an xy-scatter plot with individual point size/coloring/labeling.🖖🧐
First plot is datasheet memory bandwidth vs. FP32 TFlops/s, second plot is #FluidX3D performance vs. bandwidth, for lots of #GPU/#CPU hardware. -
Some experimentation with ```mermaid ...``` charts in #GitHub #markdown. Turns out you can hack the formatting on the quadrantChart to turn it into an xy-scatter plot with individual point size/coloring/labeling.🖖🧐
First plot is datasheet memory bandwidth vs. FP32 TFlops/s, second plot is #FluidX3D performance vs. bandwidth, for lots of #GPU/#CPU hardware. -
Some experimentation with ```mermaid ...``` charts in #GitHub #markdown. Turns out you can hack the formatting on the quadrantChart to turn it into an xy-scatter plot with individual point size/coloring/labeling.🖖🧐
First plot is datasheet memory bandwidth vs. FP32 TFlops/s, second plot is #FluidX3D performance vs. bandwidth, for lots of #GPU/#CPU hardware. -
Here's me demoing #Intel Arc Pro B60 #GPU workstations at #SC25 in St. Louis, runnig SolidWorks and #FluidX3D! 🖖😎
https://www.youtube.com/watch?v=Z8yxiyXTi7I -
Here's me demoing #Intel Arc Pro B60 #GPU workstations at #SC25 in St. Louis, runnig SolidWorks and #FluidX3D! 🖖😎
https://www.youtube.com/watch?v=Z8yxiyXTi7I -
Here's me demoing #Intel Arc Pro B60 #GPU workstations at #SC25 in St. Louis, runnig SolidWorks and #FluidX3D! 🖖😎
https://www.youtube.com/watch?v=Z8yxiyXTi7I -
Here's me demoing #Intel Arc Pro B60 #GPU workstations at #SC25 in St. Louis, runnig SolidWorks and #FluidX3D! 🖖😎
https://www.youtube.com/watch?v=Z8yxiyXTi7I -
Here's me demoing #Intel Arc Pro B60 #GPU workstations at #SC25 in St. Louis, runnig SolidWorks and #FluidX3D! 🖖😎
https://www.youtube.com/watch?v=Z8yxiyXTi7I -
Making progress on >top secret #FluidX3D update< but still a long way to go 🖖🧐
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Making progress on >top secret #FluidX3D update< but still a long way to go 🖖🧐
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Making progress on >top secret #FluidX3D update< but still a long way to go 🖖🧐
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Making progress on >top secret #FluidX3D update< but still a long way to go 🖖🧐
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Making progress on >top secret #FluidX3D update< but still a long way to go 🖖🧐
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#SC25 in wonderful St. Louis was a blast! I showcased this FluidX3D-on-Arc-Pro workstation demo there, met so many friends, had exciting conversations with all sorts of #HPC enthusiasts. And I finally saw the Cardinals - the bright red/brown birds that became the symbol of the city's famous Baseball team. 🐦
This is Flynn's #Tron Light Cycle simulated in #FluidX3D #CFD, on 4x #Intel #ArcPro B60 #GPUs with 24GB VRAM each, at a massive 1.8 Billion grid cells resolution. 🖖🤠
https://www.youtube.com/watch?v=5kZ3MmNOLoE -
#SC25 in wonderful St. Louis was a blast! I showcased this FluidX3D-on-Arc-Pro workstation demo there, met so many friends, had exciting conversations with all sorts of #HPC enthusiasts. And I finally saw the Cardinals - the bright red/brown birds that became the symbol of the city's famous Baseball team. 🐦
This is Flynn's #Tron Light Cycle simulated in #FluidX3D #CFD, on 4x #Intel #ArcPro B60 #GPUs with 24GB VRAM each, at a massive 1.8 Billion grid cells resolution. 🖖🤠
https://www.youtube.com/watch?v=5kZ3MmNOLoE -
#SC25 in wonderful St. Louis was a blast! I showcased this FluidX3D-on-Arc-Pro workstation demo there, met so many friends, had exciting conversations with all sorts of #HPC enthusiasts. And I finally saw the Cardinals - the bright red/brown birds that became the symbol of the city's famous Baseball team. 🐦
This is Flynn's #Tron Light Cycle simulated in #FluidX3D #CFD, on 4x #Intel #ArcPro B60 #GPUs with 24GB VRAM each, at a massive 1.8 Billion grid cells resolution. 🖖🤠
https://www.youtube.com/watch?v=5kZ3MmNOLoE -
#SC25 in wonderful St. Louis was a blast! I showcased this FluidX3D-on-Arc-Pro workstation demo there, met so many friends, had exciting conversations with all sorts of #HPC enthusiasts. And I finally saw the Cardinals - the bright red/brown birds that became the symbol of the city's famous Baseball team. 🐦
This is Flynn's #Tron Light Cycle simulated in #FluidX3D #CFD, on 4x #Intel #ArcPro B60 #GPUs with 24GB VRAM each, at a massive 1.8 Billion grid cells resolution. 🖖🤠
https://www.youtube.com/watch?v=5kZ3MmNOLoE -
#SC25 in wonderful St. Louis was a blast! I showcased this FluidX3D-on-Arc-Pro workstation demo there, met so many friends, had exciting conversations with all sorts of #HPC enthusiasts. And I finally saw the Cardinals - the bright red/brown birds that became the symbol of the city's famous Baseball team. 🐦
This is Flynn's #Tron Light Cycle simulated in #FluidX3D #CFD, on 4x #Intel #ArcPro B60 #GPUs with 24GB VRAM each, at a massive 1.8 Billion grid cells resolution. 🖖🤠
https://www.youtube.com/watch?v=5kZ3MmNOLoE