#parallelcomputing — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #parallelcomputing, aggregated by home.social.
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We had a very productive F2F meeting last week at the Argonne Leadership Computing Facility, with many thanks to our great hosts at the Argonne National Lab. The main objective was to feature-freeze OpenMP API version 6.1 and we accomplished that mission!
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We had a very productive F2F meeting last week at the Argonne Leadership Computing Facility, with many thanks to our great hosts at the Argonne National Lab. The main objective was to feature-freeze OpenMP API version 6.1 and we accomplished that mission!
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We had a very productive F2F meeting last week at the Argonne Leadership Computing Facility, with many thanks to our great hosts at the Argonne National Lab. The main objective was to feature-freeze OpenMP API version 6.1 and we accomplished that mission!
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We had a very productive F2F meeting last week at the Argonne Leadership Computing Facility, with many thanks to our great hosts at the Argonne National Lab. The main objective was to feature-freeze OpenMP API version 6.1 and we accomplished that mission!
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Sharing big R objects across processes shouldn’t mean copying them over and over.
mori uses shared memory + ALTREP to give you zero-copy access—multiple processes, one underlying object.
Fast, memory-efficient, and built for modern parallel workflows.
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https://www.europesays.com/people/47945/ IEEE Celebrates Global Engineering and Technology Excellence at 2026 Honors Ceremony #ChrisAMalachowsky #engineering #IEEE #IEEEMedalOfHonor #JensenHuang #MaryEllenRandall #ParallelComputing
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The OpenMP Architecture Review Board has formed a #Python Language Subcommittee — a significant step toward bringing standardized shared-memory parallelism to the world's most widely used programming language.
The subcommittee's goal is to define #OpenMP directive support for Python and include it in the OpenMP API 7.0 specification, targeted for 2029.
https://www.openmp.org/2026/python-subcomittee/
#HPC #parallelcomputing -
The OpenMP Architecture Review Board has formed a #Python Language Subcommittee — a significant step toward bringing standardized shared-memory parallelism to the world's most widely used programming language.
The subcommittee's goal is to define #OpenMP directive support for Python and include it in the OpenMP API 7.0 specification, targeted for 2029.
https://www.openmp.org/2026/python-subcomittee/
#HPC #parallelcomputing -
The OpenMP Architecture Review Board has formed a #Python Language Subcommittee — a significant step toward bringing standardized shared-memory parallelism to the world's most widely used programming language.
The subcommittee's goal is to define #OpenMP directive support for Python and include it in the OpenMP API 7.0 specification, targeted for 2029.
https://www.openmp.org/2026/python-subcomittee/
#HPC #parallelcomputing -
The OpenMP Architecture Review Board has formed a #Python Language Subcommittee — a significant step toward bringing standardized shared-memory parallelism to the world's most widely used programming language.
The subcommittee's goal is to define #OpenMP directive support for Python and include it in the OpenMP API 7.0 specification, targeted for 2029.
https://www.openmp.org/2026/python-subcomittee/
#HPC #parallelcomputing -
The OpenMP Architecture Review Board has formed a #Python Language Subcommittee — a significant step toward bringing standardized shared-memory parallelism to the world's most widely used programming language.
The subcommittee's goal is to define #OpenMP directive support for Python and include it in the OpenMP API 7.0 specification, targeted for 2029.
https://www.openmp.org/2026/python-subcomittee/
#HPC #parallelcomputing -
🎉 Wow, #groundbreaking revelation: when you give a hungry #AI agent a buffet of GPUs, it eats faster! 🚀 Who knew? Apparently, parallel computing is a thing now. 🙄 Thanks for the 12-minute read on how technology works, we were all clueless. 😂
https://blog.skypilot.co/scaling-autoresearch/ #parallelcomputing #technews #GPUbuffet #humor #HackerNews #ngated -
Setting Up a Cluster of Tiny PCs for Parallel Computing
https://www.kenkoonwong.com/blog/parallel-computing/
#HackerNews #ParallelComputing #TinyPCs #ClusterSetup #TechInnovations #HPC
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Setting Up a Cluster of Tiny PCs for Parallel Computing
https://www.kenkoonwong.com/blog/parallel-computing/
#HackerNews #ParallelComputing #TinyPCs #ClusterSetup #TechInnovations #HPC
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Setting Up a Cluster of Tiny PCs for Parallel Computing
https://www.kenkoonwong.com/blog/parallel-computing/
#HackerNews #ParallelComputing #TinyPCs #ClusterSetup #TechInnovations #HPC
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Setting Up a Cluster of Tiny PCs for Parallel Computing
https://www.kenkoonwong.com/blog/parallel-computing/
#HackerNews #ParallelComputing #TinyPCs #ClusterSetup #TechInnovations #HPC
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Setting Up a Cluster of Tiny PCs for Parallel Computing
https://www.kenkoonwong.com/blog/parallel-computing/
#HackerNews #ParallelComputing #TinyPCs #ClusterSetup #TechInnovations #HPC
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Questa settimana ho fatto la-due-giorni-a-Bologna 🚀🚀
Intensa di #talk ispiranti, #gadget bellissimi … e le persone hanno reso tutto davvero indimenticabile. ✨
Conosco i retroscena dell’organizzazione e i ragazzi del @grusp hanno resto tutto perfetto, leggero e spensierato .. sebbene non fosse per nulla facile 💪
E’ sempre un piacere essere accettati come #speaker ai loro eventi ❤️
Alla prossima !
#DataAnalysis #Dask #Kubernetes #ParallelComputing #Scalability #AWS #DevSecOpsDay #ContainerDay
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Questa settimana ho fatto la due giorni a Bologna di #DevSecOpsDay e #ContainerDay 🚀
Intensa di #talk ispiranti, #gadget bellissimi … e le persone hanno reso tutto davvero indimenticabile. ✨
Conosco i retroscena dell’organizzazione e i ragazzi del @grusp hanno resto tutto perfetto, leggero e spensierato .. sebbene non fosse per nulla facile 💪
E’ sempre un piacere essere accettati come #speaker ai loro eventi ❤️
Alla prossima !
#DataAnalysis #Dask #Kubernetes #ParallelComputing #Scalability
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Questa settimana ho fatto la due giorni a Bologna di #DevSecOpsDay e #ContainerDay 🚀
Intensa di #talk ispiranti, #gadget bellissimi … e le persone hanno reso tutto davvero indimenticabile. ✨
Conosco i retroscena dell’organizzazione e i ragazzi del @grusp hanno resto tutto perfetto, leggero e spensierato .. sebbene non fosse per nulla facile 💪
E’ sempre un piacere essere accettati come #speaker ai loro eventi ❤️
Alla prossima !
#DataAnalysis #Dask #Kubernetes #ParallelComputing #Scalability
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Questa settimana ho fatto la due giorni a Bologna di #DevSecOpsDay e #ContainerDay 🚀
Intensa di #talk ispiranti, #gadget bellissimi … e le persone hanno reso tutto davvero indimenticabile. ✨
Conosco i retroscena dell’organizzazione e i ragazzi del @grusp hanno resto tutto perfetto, leggero e spensierato .. sebbene non fosse per nulla facile 💪
E’ sempre un piacere essere accettati come #speaker ai loro eventi ❤️
Alla prossima !
#DataAnalysis #Dask #Kubernetes #ParallelComputing #Scalability
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Questa settimana ho fatto la-due-giorni-a-Bologna 🚀🚀
Intensa di #talk ispiranti, #gadget bellissimi … e le persone hanno reso tutto davvero indimenticabile. ✨
Conosco i retroscena dell’organizzazione e i ragazzi del @grusp hanno resto tutto perfetto, leggero e spensierato .. sebbene non fosse per nulla facile 💪
E’ sempre un piacere essere accettati come #speaker ai loro eventi ❤️
Alla prossima !
#DataAnalysis #Dask #Kubernetes #ParallelComputing #Scalability #AWS #DevSecOpsDay #ContainerDay
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Efficient GPU algorithm converts Bézier paths into renderable geometry, enabling real-time, cross-platform vector graphics rendering. https://hackernoon.com/implementing-data-parallel-stroke-to-fill-conversion-on-modern-gpus #parallelcomputing
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Efficiently convert cubic Bézier curves to Euler spirals for smoother GPU rendering and accurate parallel curve computations. https://hackernoon.com/how-to-convert-cubic-bezier-curves-into-euler-spirals-for-gpu-optimization #parallelcomputing
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Today I introduced a much-needed feature to #GPUSPH.
Our code supports multi-GPU and even multi-node, so in general if you have a large simulation you'll want to distribute it over all your GPUs using our internal support for it.
However, in some cases, you need to run a battery of simulations and your problem size isn't large enough to justify the use of more than a couple of GPUs for each simulation.
In this case, rather than running the simulations in your set serially (one after the other) using all GPUs for each, you'll want to run them in parallel, potentially even each on a single GPUs.
The idea is to find the next avaialble (set of) GPU(s) and launch a simulation on them while there are still available sets, then wait until a “slot” frees up and start the new one(s) as slots get freed.
Until now, we've been doing this manually by partitioning the set of simulations to do and start them in different shells.
There is actually a very powerful tool to achieve this on the command, line, GNU Parallel. As with all powerful tools, however, this is somewhat cumbersome to configure to get the intended result. And after Doing It Right™ one must remember the invocation magic …
So today I found some time to write a wrapper around GNU Parallel that basically (1) enumerates the available GPUs and (2) appends the appropriate --device command-line option to the invocation of GPUSPH, based on the slot number.
#GPGPU #ParallelComputing #DistributedComputing #GNUParallel
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Today I introduced a much-needed feature to #GPUSPH.
Our code supports multi-GPU and even multi-node, so in general if you have a large simulation you'll want to distribute it over all your GPUs using our internal support for it.
However, in some cases, you need to run a battery of simulations and your problem size isn't large enough to justify the use of more than a couple of GPUs for each simulation.
In this case, rather than running the simulations in your set serially (one after the other) using all GPUs for each, you'll want to run them in parallel, potentially even each on a single GPUs.
The idea is to find the next avaialble (set of) GPU(s) and launch a simulation on them while there are still available sets, then wait until a “slot” frees up and start the new one(s) as slots get freed.
Until now, we've been doing this manually by partitioning the set of simulations to do and start them in different shells.
There is actually a very powerful tool to achieve this on the command, line, GNU Parallel. As with all powerful tools, however, this is somewhat cumbersome to configure to get the intended result. And after Doing It Right™ one must remember the invocation magic …
So today I found some time to write a wrapper around GNU Parallel that basically (1) enumerates the available GPUs and (2) appends the appropriate --device command-line option to the invocation of GPUSPH, based on the slot number.
#GPGPU #ParallelComputing #DistributedComputing #GNUParallel
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Today I introduced a much-needed feature to #GPUSPH.
Our code supports multi-GPU and even multi-node, so in general if you have a large simulation you'll want to distribute it over all your GPUs using our internal support for it.
However, in some cases, you need to run a battery of simulations and your problem size isn't large enough to justify the use of more than a couple of GPUs for each simulation.
In this case, rather than running the simulations in your set serially (one after the other) using all GPUs for each, you'll want to run them in parallel, potentially even each on a single GPUs.
The idea is to find the next avaialble (set of) GPU(s) and launch a simulation on them while there are still available sets, then wait until a “slot” frees up and start the new one(s) as slots get freed.
Until now, we've been doing this manually by partitioning the set of simulations to do and start them in different shells.
There is actually a very powerful tool to achieve this on the command, line, GNU Parallel. As with all powerful tools, however, this is somewhat cumbersome to configure to get the intended result. And after Doing It Right™ one must remember the invocation magic …
So today I found some time to write a wrapper around GNU Parallel that basically (1) enumerates the available GPUs and (2) appends the appropriate --device command-line option to the invocation of GPUSPH, based on the slot number.
#GPGPU #ParallelComputing #DistributedComputing #GNUParallel
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Today I introduced a much-needed feature to #GPUSPH.
Our code supports multi-GPU and even multi-node, so in general if you have a large simulation you'll want to distribute it over all your GPUs using our internal support for it.
However, in some cases, you need to run a battery of simulations and your problem size isn't large enough to justify the use of more than a couple of GPUs for each simulation.
In this case, rather than running the simulations in your set serially (one after the other) using all GPUs for each, you'll want to run them in parallel, potentially even each on a single GPUs.
The idea is to find the next avaialble (set of) GPU(s) and launch a simulation on them while there are still available sets, then wait until a “slot” frees up and start the new one(s) as slots get freed.
Until now, we've been doing this manually by partitioning the set of simulations to do and start them in different shells.
There is actually a very powerful tool to achieve this on the command, line, GNU Parallel. As with all powerful tools, however, this is somewhat cumbersome to configure to get the intended result. And after Doing It Right™ one must remember the invocation magic …
So today I found some time to write a wrapper around GNU Parallel that basically (1) enumerates the available GPUs and (2) appends the appropriate --device command-line option to the invocation of GPUSPH, based on the slot number.
#GPGPU #ParallelComputing #DistributedComputing #GNUParallel
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Today I introduced a much-needed feature to #GPUSPH.
Our code supports multi-GPU and even multi-node, so in general if you have a large simulation you'll want to distribute it over all your GPUs using our internal support for it.
However, in some cases, you need to run a battery of simulations and your problem size isn't large enough to justify the use of more than a couple of GPUs for each simulation.
In this case, rather than running the simulations in your set serially (one after the other) using all GPUs for each, you'll want to run them in parallel, potentially even each on a single GPUs.
The idea is to find the next avaialble (set of) GPU(s) and launch a simulation on them while there are still available sets, then wait until a “slot” frees up and start the new one(s) as slots get freed.
Until now, we've been doing this manually by partitioning the set of simulations to do and start them in different shells.
There is actually a very powerful tool to achieve this on the command, line, GNU Parallel. As with all powerful tools, however, this is somewhat cumbersome to configure to get the intended result. And after Doing It Right™ one must remember the invocation magic …
So today I found some time to write a wrapper around GNU Parallel that basically (1) enumerates the available GPUs and (2) appends the appropriate --device command-line option to the invocation of GPUSPH, based on the slot number.
#GPGPU #ParallelComputing #DistributedComputing #GNUParallel
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We are excited to return to Supercomputing! Join us on Sunday, November 16th for the OpenMP tutorial, Mastering OpenMP Tasking. This tutorial will provide performance and scalability recipes to improve the performance of OpenMP tasking applications.
Learn more about all of OpenMP's activities at #SC25 at: https://www.openmp.org/events/sc25/
#OpenMP #Tasking #parallelcomputing #hpc #multiprocessor -
Join us at Supercomputing 2025 in St. Louis!
We have a packed agenda at this year's show with BOFs and tutorials, and be sure to join us in booth #911 to meet with OpenMP experts to ask your toughest questions, enter the daily Book Drawing, get your free OpenMP API 6.0 reference guide, and have an afternoon beverage.
Learn more: https://www.openmp.org/events/sc25/
#SC25 #OpenMP #parallelcomputing #hpc #gpu #pyomp -
Join us at Supercomputing 2025 in St. Louis!
We have a packed agenda at this year's show with BOFs and tutorials, and be sure to join us in booth #911 to meet with OpenMP experts to ask your toughest questions, enter the daily Book Drawing, get your free OpenMP API 6.0 reference guide, and have an afternoon beverage.
Learn more: https://www.openmp.org/events/sc25/
#SC25 #OpenMP #parallelcomputing #hpc #gpu #pyomp -
Wir freuen uns, Euch auch in diesem Jahr wieder spannende MATLAB-Kurse im Online-Format in der GWDG Academy anzubieten, welche von MathWorks-Mitarbeitern durchgeführt werden:
💠 Parallel Computing with MATLAB
Termin: 17.11.2025, 10:00 – 13:00 Uhr
💠 Demo Session: Scaling up MATLAB to the GWDG Scientific Compute Cluster
Termin: 19.11.2025, 15:00 – 16:30 Uhr
💠 Introduction to Research Software Development with MATLAB
Termin: 20.11.2025, 09:00 – 12:00 Uhr
💠 Connecting MATLAB with Python and other Open Source Tools
Termin: 20.11.2025 14:00 – 17:00 UhrDie Kurstermine werden ergänzt um eine sogenannte Office Hour (online) am 21.11.2025, 14:00 – 15:00 Uhr, während der Fragen zu den vorgestellten Themen der Kurse ausgiebig gestellt und behandelt werden können, um einen Austausch zwischen den Teilnehmer*innen und den Dozenten zu erreichen.
#gwdg #academy #gwdgacademy #kurs #matlab #parallelcomputing #göttingen #unigöttingen #mathswork
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Accelerated Game of Life with CUDA / Triton
https://www.boristhebrave.com/2025/09/11/accelerated-game-of-life-with-cuda-triton/
#HackerNews #AcceleratedGameOfLife #CUDA #Triton #GamingTech #ParallelComputing
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GPUPrefixSums – state of the art GPU prefix sum algorithms
https://github.com/b0nes164/GPUPrefixSums
#HackerNews #GPUPrefixSums #GPUAlgorithms #PrefixSum #ParallelComputing #DataStructures
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📢 OpenMP Newsletter – July 2025 Edition
Highlights:
🗓️ IWOMP 2025 preliminary program
👥 3 new members join the OpenMP Architecture Review Board
🛠️ OpenMP support in:* GCC 15.1
* Intel oneAPI HPC Toolkit 2025.2
* NumPy 2.3
Full newsletter: https://mailchi.mp/e82391a1d7b0/thanks-for-your-interest-in-openmp-17461513
#OpenMP #HPC #IWOMP2025 #ParallelComputing #NumPy #GCC #InteloneAPI
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📢 OpenMP Newsletter – July 2025 Edition
Highlights:
🗓️ IWOMP 2025 preliminary program
👥 3 new members join the OpenMP Architecture Review Board
🛠️ OpenMP support in:* GCC 15.1
* Intel oneAPI HPC Toolkit 2025.2
* NumPy 2.3
Full newsletter: https://mailchi.mp/e82391a1d7b0/thanks-for-your-interest-in-openmp-17461513
#OpenMP #HPC #IWOMP2025 #ParallelComputing #NumPy #GCC #InteloneAPI
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📢 OpenMP Newsletter – July 2025 Edition
Highlights:
🗓️ IWOMP 2025 preliminary program
👥 3 new members join the OpenMP Architecture Review Board
🛠️ OpenMP support in:* GCC 15.1
* Intel oneAPI HPC Toolkit 2025.2
* NumPy 2.3
Full newsletter: https://mailchi.mp/e82391a1d7b0/thanks-for-your-interest-in-openmp-17461513
#OpenMP #HPC #IWOMP2025 #ParallelComputing #NumPy #GCC #InteloneAPI
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📢 OpenMP Newsletter – July 2025 Edition
Highlights:
🗓️ IWOMP 2025 preliminary program
👥 3 new members join the OpenMP Architecture Review Board
🛠️ OpenMP support in:* GCC 15.1
* Intel oneAPI HPC Toolkit 2025.2
* NumPy 2.3
Full newsletter: https://mailchi.mp/e82391a1d7b0/thanks-for-your-interest-in-openmp-17461513
#OpenMP #HPC #IWOMP2025 #ParallelComputing #NumPy #GCC #InteloneAPI
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📢 OpenMP Newsletter – July 2025 Edition
Highlights:
🗓️ IWOMP 2025 preliminary program
👥 3 new members join the OpenMP Architecture Review Board
🛠️ OpenMP support in:* GCC 15.1
* Intel oneAPI HPC Toolkit 2025.2
* NumPy 2.3
Full newsletter: https://mailchi.mp/e82391a1d7b0/thanks-for-your-interest-in-openmp-17461513
#OpenMP #HPC #IWOMP2025 #ParallelComputing #NumPy #GCC #InteloneAPI
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Going to the (Parallel) Chapel - There is always the promise of using more computing power for a single task. Your ... - https://hackaday.com/2025/07/06/going-to-the-parallel-chapel/ #softwaredevelopment #parallelcomputing
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Calculating the Fibonacci numbers on GPU
https://veitner.bearblog.dev/calculating-the-fibonacci-numbers-on-gpu/
#HackerNews #Calculating #Fibonacci #GPU #Performance #ParallelComputing #TechInnovation #Algorithms
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📸 Full house at the OpenMP BOF at #ISC25 — over 140 attendees joined us in Hamburg! 🎉
Our session "What to Expect from OpenMP API Version 6.0" covered:
✅ A dive into key features of OpenMP 6.0
✅ A preview of 6.1 and 7.0
✅ Updates from toolchain developers
✅ Lively Q&A to help shape future OpenMP directionsThanks to everyone who contributed — your feedback is powering the future of parallel programming! 💡
#OpenMP #HPC #ISC2025 #OpenMP6 #ParallelComputing #Supercomputing
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📸 Full house at the OpenMP BOF at #ISC25 — over 140 attendees joined us in Hamburg! 🎉
Our session "What to Expect from OpenMP API Version 6.0" covered:
✅ A dive into key features of OpenMP 6.0
✅ A preview of 6.1 and 7.0
✅ Updates from toolchain developers
✅ Lively Q&A to help shape future OpenMP directionsThanks to everyone who contributed — your feedback is powering the future of parallel programming! 💡
#OpenMP #HPC #ISC2025 #OpenMP6 #ParallelComputing #Supercomputing
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📸 Full house at the OpenMP BOF at #ISC25 — over 140 attendees joined us in Hamburg! 🎉
Our session "What to Expect from OpenMP API Version 6.0" covered:
✅ A dive into key features of OpenMP 6.0
✅ A preview of 6.1 and 7.0
✅ Updates from toolchain developers
✅ Lively Q&A to help shape future OpenMP directionsThanks to everyone who contributed — your feedback is powering the future of parallel programming! 💡
#OpenMP #HPC #ISC2025 #OpenMP6 #ParallelComputing #Supercomputing
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📸 Full house at the OpenMP BOF at #ISC25 — over 140 attendees joined us in Hamburg! 🎉
Our session "What to Expect from OpenMP API Version 6.0" covered:
✅ A dive into key features of OpenMP 6.0
✅ A preview of 6.1 and 7.0
✅ Updates from toolchain developers
✅ Lively Q&A to help shape future OpenMP directionsThanks to everyone who contributed — your feedback is powering the future of parallel programming! 💡
#OpenMP #HPC #ISC2025 #OpenMP6 #ParallelComputing #Supercomputing
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📸 Full house at the OpenMP BOF at #ISC25 — over 140 attendees joined us in Hamburg! 🎉
Our session "What to Expect from OpenMP API Version 6.0" covered:
✅ A dive into key features of OpenMP 6.0
✅ A preview of 6.1 and 7.0
✅ Updates from toolchain developers
✅ Lively Q&A to help shape future OpenMP directionsThanks to everyone who contributed — your feedback is powering the future of parallel programming! 💡
#OpenMP #HPC #ISC2025 #OpenMP6 #ParallelComputing #Supercomputing
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We’re excited to welcome NextSilicon to the OpenMP Architecture Review Board! 🎉
Their Intelligent Compute Architecture blends adaptive computing with self-optimizing hardware/software and open frameworks like OpenMP. Together, we’re shaping a future of performant, portable, shared-memory parallelism. 💻🌐
Read the press release:
https://tinyurl.com/yksfbrah
