"The Distributed Oceanographic Match-up Service (DOMS) is a
web-accessible service tool that will reconcile satellite and in situ
datasets in support of NASA’s Earth Science mission. The service will
provide a mechanism for users to input a series of geospatial references
for satellite observations (e.g., footprint location, date, and time)
and receive the in-situ observations that are “matched” to the satellite
data within a selectable temporal and spatial domain. The inverse of
inputting in-situ geospatial data (e.g., positions of moorings, floats,
or ships) and returning corresponding satellite observations will also
be supported. The DOMS prototype will include several characteristic
in-situ and satellite observation datasets. For the in-situ data, the
focus will be surface marine observations from the International
Comprehensive Ocean-Atmosphere Data Set (ICOADS), the Shipboard
Automated Meteorological and Oceanographic System Initiative (SAMOS),
and the Salinity Processes in the Upper Ocean Regional Study (SPURS).
Satellite products will include JPL ASCAT winds, Aquarius orbital/swath
dataset, MODIS SST, and the high-resolution gridded MUR-SST product.
Importantly, although DOMS will be established with these selected
datasets, it will be readily extendable to other in situ and satellite
collections, which could support additional science disciplines."
https://mdc.coaps.fsu.edu/doms
https://sea.ucar.edu/event/building-distributed-oceanography-match-service-doms-pair-field-observation-and-satellite-data
Monday, September 12, 2016
GTX1070 Linux installation and mining clue
"As you might have read i got 18 GTX1070 and posted some benchmark information earlier (http://forum.ethereum.org/discussion/comment/42663). @vaulter asked to some some details (@vaulter
perhaps you can add your GTX1080 findings, settings?) In this topic i
want to place the more technical notes how you can get this working. The
short summery: Yes i managed to get 6x GTX1070 running at 218.11MH/s
with heavy tuning / overclocking, but no idea how this would hold long
term. Currently i keep them at 192,88MH/s (x3 rigs) which seem to be the
'safe overclocking defaults' to me. Who knows how stuff progresses with
updates from @Genoil
and if its running under a windows driver stable and fast. Safe to say
with the lesser power consumption AND more MH/s then a card like R9 390X
this GTX1070 with its price is a very nice card to have (especially if
you run apps that only run good on Nvidia cards)
It took me quite a while to get it working and this document only contains 5% of my notes and stuff, its the minimum to get you started and you will need to do some tuning on your own to max your card out. Some stuff aren't as good as i like yet (e.g. headless VNC access without the use of a monitor) but it works and more importantly its stable. Thanks go out to @Genoil for his clue and his work on ethminer. This document is not entirely ment as a walk-through as some knowledge on mining, linux overclocking and common sense is still required ... So here goes."
https://forum.ethereum.org/discussion/7780/gtx1070-linux-installation-and-mining-clue-goodbye-amd-welcome-nvidia-for-miners
It took me quite a while to get it working and this document only contains 5% of my notes and stuff, its the minimum to get you started and you will need to do some tuning on your own to max your card out. Some stuff aren't as good as i like yet (e.g. headless VNC access without the use of a monitor) but it works and more importantly its stable. Thanks go out to @Genoil for his clue and his work on ethminer. This document is not entirely ment as a walk-through as some knowledge on mining, linux overclocking and common sense is still required ... So here goes."
https://forum.ethereum.org/discussion/7780/gtx1070-linux-installation-and-mining-clue-goodbye-amd-welcome-nvidia-for-miners
NVIDIA GeForce GTX 1070 On Linux: Testing With OpenGL, OpenCL, CUDA & Vulkan
14 June 2016
"NVIDIA sent over a GeForce GTX 1070 and I've been putting it through its paces under Linux with a variety of OpenGL, OpenCL, and Vulkan benchmarks along with CUDA and deep learning benchmarks. Here's the first look at the GeForce GTX 1070 performance under Ubuntu Linux.
In conjunction with the NVIDIA 367 proprietary driver on Linux, the GeForce GTX 1070 ran into no difficulties running under Ubuntu Linux throughout my initial testing. As noted in my GTX 1080 Linux review, there wasn't any overclocking support available when enabling the CoolBits options and this is a similar limitation with the GTX 1070 (yesterday NVIDIA did release a new 367 Linux driver that I have yet to test but its official change-log at least didn't make note of any overclocking additions).
Since my earlier GTX 1080 review, nothing has changed with regards to the open-source driver support. I have yet to see any experimental patches published for at least kernel mode-setting in Nouveau while any accelerated support for Pascal will not happen until NVIDIA is able to release the signed firmware binary images for usage by the Nouveau driver. I haven't received any word from NVIDIA Corp yet when that Pascal firmware availability is expected, but at least the proprietary driver support is in good shape.
...
Well, that's all the initial data I have to share on the GeForce GTX 1070 after hammering it under Linux the past 24 hours. The GeForce GTX 1070 is a very nice upgrade over the GeForce GTX 900 series and especially if you are still using a Kepler graphics card or later. In many of our Linux benchmarks, the GeForce GTX 1070 was around 60% faster than the GTX 970! The GTX 1070 was commonly beating the GTX 980 Ti and GTX TITAN X while the GeForce GTX 1080 still delivers the maximum performance possible for a desktop graphics card at this time. The GTX 1070 (and GTX 1080) aren't only stunning for their raw performance but the power efficiency is also a significant push forward. Particularly when the GeForce GTX 1070 AIB cards begin appearing in the coming weeks at $399, the GeForce GTX 1070 should be a very nice option for Linux gamers looking to get the maximum performance for 1440p or 4K gaming. It will be fun to see later this month how the Radeon RX 480 compares, but considering the state of the Radeon Linux drivers, chances are you'll want to stick to the green side for the best Linux gaming experience unless you are a devout user of open-source drivers."
http://www.phoronix.com/scan.php?page=article&item=nvidia-gtx-1070&num=1
http://www.nvidia.com/download/driverresults.aspx/104284/en-us
"NVIDIA sent over a GeForce GTX 1070 and I've been putting it through its paces under Linux with a variety of OpenGL, OpenCL, and Vulkan benchmarks along with CUDA and deep learning benchmarks. Here's the first look at the GeForce GTX 1070 performance under Ubuntu Linux.
In conjunction with the NVIDIA 367 proprietary driver on Linux, the GeForce GTX 1070 ran into no difficulties running under Ubuntu Linux throughout my initial testing. As noted in my GTX 1080 Linux review, there wasn't any overclocking support available when enabling the CoolBits options and this is a similar limitation with the GTX 1070 (yesterday NVIDIA did release a new 367 Linux driver that I have yet to test but its official change-log at least didn't make note of any overclocking additions).
Since my earlier GTX 1080 review, nothing has changed with regards to the open-source driver support. I have yet to see any experimental patches published for at least kernel mode-setting in Nouveau while any accelerated support for Pascal will not happen until NVIDIA is able to release the signed firmware binary images for usage by the Nouveau driver. I haven't received any word from NVIDIA Corp yet when that Pascal firmware availability is expected, but at least the proprietary driver support is in good shape.
...
Well, that's all the initial data I have to share on the GeForce GTX 1070 after hammering it under Linux the past 24 hours. The GeForce GTX 1070 is a very nice upgrade over the GeForce GTX 900 series and especially if you are still using a Kepler graphics card or later. In many of our Linux benchmarks, the GeForce GTX 1070 was around 60% faster than the GTX 970! The GTX 1070 was commonly beating the GTX 980 Ti and GTX TITAN X while the GeForce GTX 1080 still delivers the maximum performance possible for a desktop graphics card at this time. The GTX 1070 (and GTX 1080) aren't only stunning for their raw performance but the power efficiency is also a significant push forward. Particularly when the GeForce GTX 1070 AIB cards begin appearing in the coming weeks at $399, the GeForce GTX 1070 should be a very nice option for Linux gamers looking to get the maximum performance for 1440p or 4K gaming. It will be fun to see later this month how the Radeon RX 480 compares, but considering the state of the Radeon Linux drivers, chances are you'll want to stick to the green side for the best Linux gaming experience unless you are a devout user of open-source drivers."
http://www.phoronix.com/scan.php?page=article&item=nvidia-gtx-1070&num=1
http://www.nvidia.com/download/driverresults.aspx/104284/en-us
Sunday, September 11, 2016
pymp
"This package brings OpenMP-like functionality to Python. It takes the good qualities of OpenMP such as minimal code changes and high efficiency and combines them with the Python Zen of code clarity and ease-of-use."
MetaMoprh
"A library framework designed to (automatically) extract as much computational capability as possible from HPC systems. Its design centers around three core principles: abstraction, interoperability, and adaptivity.
We realize MetaMorph2 as a layered library of libraries. Each tier implements one of the core principles of abstraction, interoperability, and adaptivity. The top-level user APIs and platform-specific back-ends exists as separate shared library objects, with interfaces designated in shared header files. Primarily, this encapsulation supports custom tuning of backends to a specific device or class of devices. In addition, it allows back-ends to be separately used, distributed, compiled, or even completely rewritten, without interference with the other components.
The core API, library infrastructure and communication interface are written in standard C for portability and performance. Individual accelerator back-ends are generated in C with OpenMP and optional SIMD extensions (for CPU and Intel MIC), CUDA C/C++ (NVIDIA GPUs), and C++ with OpenCL (AMD GPUs/APUs and other devices). In addition, a wrapper around the top-level API is written in polymorphic Fortran 2003 to simplify interoperability with Fortran applications prevalent in some fields of scientific computing."
http://synergy.cs.vt.edu/
https://github.com/vtsynergy/MetaMorph
MetaMorph: A Library Framework for Interoperable Kernels on Multi- and Many-core Clusters - http://hgpu.org/?p=16446
We realize MetaMorph2 as a layered library of libraries. Each tier implements one of the core principles of abstraction, interoperability, and adaptivity. The top-level user APIs and platform-specific back-ends exists as separate shared library objects, with interfaces designated in shared header files. Primarily, this encapsulation supports custom tuning of backends to a specific device or class of devices. In addition, it allows back-ends to be separately used, distributed, compiled, or even completely rewritten, without interference with the other components.
The core API, library infrastructure and communication interface are written in standard C for portability and performance. Individual accelerator back-ends are generated in C with OpenMP and optional SIMD extensions (for CPU and Intel MIC), CUDA C/C++ (NVIDIA GPUs), and C++ with OpenCL (AMD GPUs/APUs and other devices). In addition, a wrapper around the top-level API is written in polymorphic Fortran 2003 to simplify interoperability with Fortran applications prevalent in some fields of scientific computing."
http://synergy.cs.vt.edu/
https://github.com/vtsynergy/MetaMorph
MetaMorph: A Library Framework for Interoperable Kernels on Multi- and Many-core Clusters - http://hgpu.org/?p=16446
Software Heritage
"Our ambition is to collect, preserve, and share all software that is publicly available in source code form. On this foundation, a wealth of applications can be built, ranging from cultural heritage to industry and research.
Software is an essential part of our lives. Given that any software component may turn out to be essential in the future, we do not make distinctions and collect all software that is publicly available in source code form.
We recognize that there is significant value in selecting among all this software some collections of particular interest, and we will encourage the construction of curated archives on top of Software Heritage.
We keep track of the origin of software we archive and store its full development history: this precious meta-information will be carefully harvested and structured for future use."
https://www.softwareheritage.org/
Software is an essential part of our lives. Given that any software component may turn out to be essential in the future, we do not make distinctions and collect all software that is publicly available in source code form.
We recognize that there is significant value in selecting among all this software some collections of particular interest, and we will encourage the construction of curated archives on top of Software Heritage.
We keep track of the origin of software we archive and store its full development history: this precious meta-information will be carefully harvested and structured for future use."
https://www.softwareheritage.org/
Gaalop
"Gaalop (Geometic Algebra Algorithms Optimizer) is a software to optimize geometric algebra files.
Algorithms can be developed by using the freely available CLUCalc software by Christian Perwass. Gaalop optimizes the algorithm and produces C++ (AMP), OpenCL, CUDA, CLUCalc or LaTeX output (other output-formats will follow)."
http://www.gaalop.de/
https://github.com/CallForSanity/Gaalop
Gaalop – High Performance Parallel Computing based on Conformal Geometric Algebra - http://www.gaalop.de/wp-content/uploads/Gaalop-High-PerformanceComputing-based-onConformal-Geometric-Algebra.pdf
Geometric Algebra Enhanced Precompiler for C++, OpenCL and Mathematica’s OpenCLLink - http://hgpu.org/?p=12044
Algorithms can be developed by using the freely available CLUCalc software by Christian Perwass. Gaalop optimizes the algorithm and produces C++ (AMP), OpenCL, CUDA, CLUCalc or LaTeX output (other output-formats will follow)."
http://www.gaalop.de/
https://github.com/CallForSanity/Gaalop
Gaalop – High Performance Parallel Computing based on Conformal Geometric Algebra - http://www.gaalop.de/wp-content/uploads/Gaalop-High-PerformanceComputing-based-onConformal-Geometric-Algebra.pdf
Geometric Algebra Enhanced Precompiler for C++, OpenCL and Mathematica’s OpenCLLink - http://hgpu.org/?p=12044
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