BranchesTags

Latest commit

History

136 Commits

Folders and files

NameName
Last commit message
Last commit date
R
R
man
man
src
src
.Rbuildignore
.Rbuildignore
.gitignore
.gitignore
DESCRIPTION
DESCRIPTION
NAMESPACE
NAMESPACE
README.md
README.md

Repository files navigation

DOI

Purpose

The fbseqCUDA package is an internal backend of fbseq package that runs the Markov chain Monte Carlo (MCMC) procedure behind the scenes. It is implemented with CUDA for acceleration with parallel computing. For installation, CUDA must be installed. To use fbseqCUDA package in an MCMC, fbseq package must be installed, and a CUDA-capable general-purpose graphics processing unit (GPU) must be installed on your machine.

System requirements

  • The R version and R packages listed in the "Depends", "Imports", and "Suggests" fields of the "package's DESCRIPTION file.
  • A CUDA-capable NVIDIA graphics processing unit (GPU) with compute capability 2.0 or greater.
  • CUDA version 6.0 or greater. More information about CUDA is available through NVIDIA.
  • Optional: the code uses double precision values for computation, so GPUs that natively support double precision will be much faster than ones that do not.

Installation

Option 1: install a stable release (recommended).

Navigate to a list of stable releases on the project's GitHub page. Download the desired tar.gz bundle, then install it either with install.packages(..., repos = NULL, type="source") from within R R CMD INSTALL from the Unix/Linux command line.

Option 2: use install_github to install the development version.

For this option, you need the devtools package, available from CRAN or GitHub. Open R and run

library(devtools)
install_github("wlandau/fbseqCUDA")

Option 3: build the development version from the source.

Open a command line program such as Terminal in Mac/Linux and enter the following commands.

git clone git@github.com:wlandau/fbseqCUDA.git
R CMD build fbseqCUDA
R CMD INSTALL ...

where ... is replaced by the name of the tarball produced by R CMD build.

Troubleshooting

If CUDA is not found, open fbseqCUDA/src/Makevars in a text editor. The top line reads

CUDA_HOME = /usr/local/cuda

but this may not be correct for your system. Replace /usr/local/cuda with the correct path to the installation of CUDA on your computer.

About

CUDA-accelerated backend of fbseq for the MCMC.

Resources

Readme
Activity
Custom properties

Stars

0 stars

Watchers

1 watching

Forks

0 forks
Report repository

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
BranchesTags
Latest commit
History
136 Commits
Folders and files
NameName
Last commit message
Last commit date
R
R
man
man
src
src
.Rbuildignore
.Rbuildignore
.gitignore
.gitignore
DESCRIPTION
DESCRIPTION
NAMESPACE
NAMESPACE
README.md
README.md
Repository files navigation
DOI
Purpose
The fbseqCUDA package is an internal backend of fbseq package that runs the Markov chain Monte Carlo (MCMC) procedure behind the scenes. It is implemented with CUDA for acceleration with parallel computing. For installation, CUDA must be installed. To use fbseqCUDA package in an MCMC, fbseq package must be installed, and a CUDA-capable general-purpose graphics processing unit (GPU) must be installed on your machine.
System requirements
  • The R version and R packages listed in the "Depends", "Imports", and "Suggests" fields of the "package's DESCRIPTION file.
  • A CUDA-capable NVIDIA graphics processing unit (GPU) with compute capability 2.0 or greater.
  • CUDA version 6.0 or greater. More information about CUDA is available through NVIDIA.
  • Optional: the code uses double precision values for computation, so GPUs that natively support double precision will be much faster than ones that do not.
Installation
Option 1: install a stable release (recommended).
Navigate to a list of stable releases on the project's GitHub page. Download the desired tar.gz bundle, then install it either with install.packages(..., repos = NULL, type="source") from within R R CMD INSTALL from the Unix/Linux command line.
Option 2: use install_github to install the development version.
For this option, you need the devtools package, available from CRAN or GitHub. Open R and run
library(devtools)
install_github("wlandau/fbseqCUDA")

Option 3: build the development version from the source.
Open a command line program such as Terminal in Mac/Linux and enter the following commands.
git clone git@github.com:wlandau/fbseqCUDA.git
R CMD build fbseqCUDA
R CMD INSTALL ...

where ... is replaced by the name of the tarball produced by R CMD build.
Troubleshooting
If CUDA is not found, open fbseqCUDA/src/Makevars in a text editor. The top line reads
CUDA_HOME = /usr/local/cuda

but this may not be correct for your system. Replace /usr/local/cuda with the correct path to the installation of CUDA on your computer.
About
CUDA-accelerated backend of fbseq for the MCMC.
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Latest commit
History
136 Commits
Folders and files
NameName
Last commit message
Last commit date
R
R
man
man
src
src
.Rbuildignore
.Rbuildignore
.gitignore
.gitignore
DESCRIPTION
DESCRIPTION
NAMESPACE
NAMESPACE
README.md
README.md
Repository files navigation
DOI
Purpose
The fbseqCUDA package is an internal backend of fbseq package that runs the Markov chain Monte Carlo (MCMC) procedure behind the scenes. It is implemented with CUDA for acceleration with parallel computing. For installation, CUDA must be installed. To use fbseqCUDA package in an MCMC, fbseq package must be installed, and a CUDA-capable general-purpose graphics processing unit (GPU) must be installed on your machine.
System requirements
  • The R version and R packages listed in the "Depends", "Imports", and "Suggests" fields of the "package's DESCRIPTION file.
  • A CUDA-capable NVIDIA graphics processing unit (GPU) with compute capability 2.0 or greater.
  • CUDA version 6.0 or greater. More information about CUDA is available through NVIDIA.
  • Optional: the code uses double precision values for computation, so GPUs that natively support double precision will be much faster than ones that do not.
Installation
Option 1: install a stable release (recommended).
Navigate to a list of stable releases on the project's GitHub page. Download the desired tar.gz bundle, then install it either with install.packages(..., repos = NULL, type="source") from within R R CMD INSTALL from the Unix/Linux command line.
Option 2: use install_github to install the development version.
For this option, you need the devtools package, available from CRAN or GitHub. Open R and run
library(devtools)
install_github("wlandau/fbseqCUDA")

Option 3: build the development version from the source.
Open a command line program such as Terminal in Mac/Linux and enter the following commands.
git clone git@github.com:wlandau/fbseqCUDA.git
R CMD build fbseqCUDA
R CMD INSTALL ...

where ... is replaced by the name of the tarball produced by R CMD build.
Troubleshooting
If CUDA is not found, open fbseqCUDA/src/Makevars in a text editor. The top line reads
CUDA_HOME = /usr/local/cuda

but this may not be correct for your system. Replace /usr/local/cuda with the correct path to the installation of CUDA on your computer.
About
CUDA-accelerated backend of fbseq for the MCMC.
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Latest commit
History
136 Commits
Folders and files
NameName
Last commit message
Last commit date
R
R
man
man
src
src
.Rbuildignore
.Rbuildignore
.gitignore
.gitignore
DESCRIPTION
DESCRIPTION
NAMESPACE
NAMESPACE
README.md
README.md
Repository files navigation
DOI
Purpose
The fbseqCUDA package is an internal backend of fbseq package that runs the Markov chain Monte Carlo (MCMC) procedure behind the scenes. It is implemented with CUDA for acceleration with parallel computing. For installation, CUDA must be installed. To use fbseqCUDA package in an MCMC, fbseq package must be installed, and a CUDA-capable general-purpose graphics processing unit (GPU) must be installed on your machine.
System requirements
  • The R version and R packages listed in the "Depends", "Imports", and "Suggests" fields of the "package's DESCRIPTION file.
  • A CUDA-capable NVIDIA graphics processing unit (GPU) with compute capability 2.0 or greater.
  • CUDA version 6.0 or greater. More information about CUDA is available through NVIDIA.
  • Optional: the code uses double precision values for computation, so GPUs that natively support double precision will be much faster than ones that do not.
Installation
Option 1: install a stable release (recommended).
Navigate to a list of stable releases on the project's GitHub page. Download the desired tar.gz bundle, then install it either with install.packages(..., repos = NULL, type="source") from within R R CMD INSTALL from the Unix/Linux command line.
Option 2: use install_github to install the development version.
For this option, you need the devtools package, available from CRAN or GitHub. Open R and run
library(devtools)
install_github("wlandau/fbseqCUDA")

Option 3: build the development version from the source.
Open a command line program such as Terminal in Mac/Linux and enter the following commands.
git clone git@github.com:wlandau/fbseqCUDA.git
R CMD build fbseqCUDA
R CMD INSTALL ...

where ... is replaced by the name of the tarball produced by R CMD build.
Troubleshooting
If CUDA is not found, open fbseqCUDA/src/Makevars in a text editor. The top line reads
CUDA_HOME = /usr/local/cuda

but this may not be correct for your system. Replace /usr/local/cuda with the correct path to the installation of CUDA on your computer.
About
CUDA-accelerated backend of fbseq for the MCMC.
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Latest commit
History
136 Commits
Folders and files
NameName
Last commit message
Last commit date
R
R
man
man
src
src
.Rbuildignore
.Rbuildignore
.gitignore
.gitignore
DESCRIPTION
DESCRIPTION
NAMESPACE
NAMESPACE
README.md
README.md
Repository files navigation
DOI
Purpose
The fbseqCUDA package is an internal backend of fbseq package that runs the Markov chain Monte Carlo (MCMC) procedure behind the scenes. It is implemented with CUDA for acceleration with parallel computing. For installation, CUDA must be installed. To use fbseqCUDA package in an MCMC, fbseq package must be installed, and a CUDA-capable general-purpose graphics processing unit (GPU) must be installed on your machine.
System requirements
  • The R version and R packages listed in the "Depends", "Imports", and "Suggests" fields of the "package's DESCRIPTION file.
  • A CUDA-capable NVIDIA graphics processing unit (GPU) with compute capability 2.0 or greater.
  • CUDA version 6.0 or greater. More information about CUDA is available through NVIDIA.
  • Optional: the code uses double precision values for computation, so GPUs that natively support double precision will be much faster than ones that do not.
Installation
Option 1: install a stable release (recommended).
Navigate to a list of stable releases on the project's GitHub page. Download the desired tar.gz bundle, then install it either with install.packages(..., repos = NULL, type="source") from within R R CMD INSTALL from the Unix/Linux command line.
Option 2: use install_github to install the development version.
For this option, you need the devtools package, available from CRAN or GitHub. Open R and run
library(devtools)
install_github("wlandau/fbseqCUDA")

Option 3: build the development version from the source.
Open a command line program such as Terminal in Mac/Linux and enter the following commands.
git clone git@github.com:wlandau/fbseqCUDA.git
R CMD build fbseqCUDA
R CMD INSTALL ...

where ... is replaced by the name of the tarball produced by R CMD build.
Troubleshooting
If CUDA is not found, open fbseqCUDA/src/Makevars in a text editor. The top line reads
CUDA_HOME = /usr/local/cuda

but this may not be correct for your system. Replace /usr/local/cuda with the correct path to the installation of CUDA on your computer.
About
CUDA-accelerated backend of fbseq for the MCMC.
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Latest commit
History
136 Commits
Folders and files
NameName
Last commit message
Last commit date
R
R
man
man
src
src
.Rbuildignore
.Rbuildignore
.gitignore
.gitignore
DESCRIPTION
DESCRIPTION
NAMESPACE
NAMESPACE
README.md
README.md
Repository files navigation
DOI
Purpose
The fbseqCUDA package is an internal backend of fbseq package that runs the Markov chain Monte Carlo (MCMC) procedure behind the scenes. It is implemented with CUDA for acceleration with parallel computing. For installation, CUDA must be installed. To use fbseqCUDA package in an MCMC, fbseq package must be installed, and a CUDA-capable general-purpose graphics processing unit (GPU) must be installed on your machine.
System requirements
  • The R version and R packages listed in the "Depends", "Imports", and "Suggests" fields of the "package's DESCRIPTION file.
  • A CUDA-capable NVIDIA graphics processing unit (GPU) with compute capability 2.0 or greater.
  • CUDA version 6.0 or greater. More information about CUDA is available through NVIDIA.
  • Optional: the code uses double precision values for computation, so GPUs that natively support double precision will be much faster than ones that do not.
Installation
Option 1: install a stable release (recommended).
Navigate to a list of stable releases on the project's GitHub page. Download the desired tar.gz bundle, then install it either with install.packages(..., repos = NULL, type="source") from within R R CMD INSTALL from the Unix/Linux command line.
Option 2: use install_github to install the development version.
For this option, you need the devtools package, available from CRAN or GitHub. Open R and run
library(devtools)
install_github("wlandau/fbseqCUDA")

Option 3: build the development version from the source.
Open a command line program such as Terminal in Mac/Linux and enter the following commands.
git clone git@github.com:wlandau/fbseqCUDA.git
R CMD build fbseqCUDA
R CMD INSTALL ...

where ... is replaced by the name of the tarball produced by R CMD build.
Troubleshooting
If CUDA is not found, open fbseqCUDA/src/Makevars in a text editor. The top line reads
CUDA_HOME = /usr/local/cuda

but this may not be correct for your system. Replace /usr/local/cuda with the correct path to the installation of CUDA on your computer.
About
CUDA-accelerated backend of fbseq for the MCMC.
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Latest commit
History
136 Commits
Folders and files
NameName
Last commit message
Last commit date
R
R
man
man
src
src
.Rbuildignore
.Rbuildignore
.gitignore
.gitignore
DESCRIPTION
DESCRIPTION
NAMESPACE
NAMESPACE
README.md
README.md
Repository files navigation
DOI
Purpose
The fbseqCUDA package is an internal backend of fbseq package that runs the Markov chain Monte Carlo (MCMC) procedure behind the scenes. It is implemented with CUDA for acceleration with parallel computing. For installation, CUDA must be installed. To use fbseqCUDA package in an MCMC, fbseq package must be installed, and a CUDA-capable general-purpose graphics processing unit (GPU) must be installed on your machine.
System requirements
  • The R version and R packages listed in the "Depends", "Imports", and "Suggests" fields of the "package's DESCRIPTION file.
  • A CUDA-capable NVIDIA graphics processing unit (GPU) with compute capability 2.0 or greater.
  • CUDA version 6.0 or greater. More information about CUDA is available through NVIDIA.
  • Optional: the code uses double precision values for computation, so GPUs that natively support double precision will be much faster than ones that do not.
Installation
Option 1: install a stable release (recommended).
Navigate to a list of stable releases on the project's GitHub page. Download the desired tar.gz bundle, then install it either with install.packages(..., repos = NULL, type="source") from within R R CMD INSTALL from the Unix/Linux command line.
Option 2: use install_github to install the development version.
For this option, you need the devtools package, available from CRAN or GitHub. Open R and run
library(devtools)
install_github("wlandau/fbseqCUDA")

Option 3: build the development version from the source.
Open a command line program such as Terminal in Mac/Linux and enter the following commands.
git clone git@github.com:wlandau/fbseqCUDA.git
R CMD build fbseqCUDA
R CMD INSTALL ...

where ... is replaced by the name of the tarball produced by R CMD build.
Troubleshooting
If CUDA is not found, open fbseqCUDA/src/Makevars in a text editor. The top line reads
CUDA_HOME = /usr/local/cuda

but this may not be correct for your system. Replace /usr/local/cuda with the correct path to the installation of CUDA on your computer.
About
CUDA-accelerated backend of fbseq for the MCMC.
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

Skip to content
BranchesTags
Latest commit
History
136 Commits
Folders and files
NameName
Last commit message
Last commit date
R
R
man
man
src
src
.Rbuildignore
.Rbuildignore
.gitignore
.gitignore
DESCRIPTION
DESCRIPTION
NAMESPACE
NAMESPACE
README.md
README.md
Repository files navigation
DOI
Purpose
The fbseqCUDA package is an internal backend of fbseq package that runs the Markov chain Monte Carlo (MCMC) procedure behind the scenes. It is implemented with CUDA for acceleration with parallel computing. For installation, CUDA must be installed. To use fbseqCUDA package in an MCMC, fbseq package must be installed, and a CUDA-capable general-purpose graphics processing unit (GPU) must be installed on your machine.
System requirements
  • The R version and R packages listed in the "Depends", "Imports", and "Suggests" fields of the "package's DESCRIPTION file.
  • A CUDA-capable NVIDIA graphics processing unit (GPU) with compute capability 2.0 or greater.
  • CUDA version 6.0 or greater. More information about CUDA is available through NVIDIA.
  • Optional: the code uses double precision values for computation, so GPUs that natively support double precision will be much faster than ones that do not.
Installation
Option 1: install a stable release (recommended).
Navigate to a list of stable releases on the project's GitHub page. Download the desired tar.gz bundle, then install it either with install.packages(..., repos = NULL, type="source") from within R R CMD INSTALL from the Unix/Linux command line.
Option 2: use install_github to install the development version.
For this option, you need the devtools package, available from CRAN or GitHub. Open R and run
library(devtools)
install_github("wlandau/fbseqCUDA")

Option 3: build the development version from the source.
Open a command line program such as Terminal in Mac/Linux and enter the following commands.
git clone git@github.com:wlandau/fbseqCUDA.git
R CMD build fbseqCUDA
R CMD INSTALL ...

where ... is replaced by the name of the tarball produced by R CMD build.
Troubleshooting
If CUDA is not found, open fbseqCUDA/src/Makevars in a text editor. The top line reads
CUDA_HOME = /usr/local/cuda

but this may not be correct for your system. Replace /usr/local/cuda with the correct path to the installation of CUDA on your computer.
About
CUDA-accelerated backend of fbseq for the MCMC.
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages