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Repository of sorting algorithms in C and CUDA.

Information

Our program generates and fills arrays in four different ways:

  1. arrays with totally random elements
  2. arrays already ordered
  3. arrays ordered in descending order
  4. arrays 90% ordered.

Sorting methods implemented

  1. Selection sort
  2. Insertion sort
  3. Shell sort
  4. Quick sort
  5. Heap sort
  6. Merge sort
  7. CUDA Quick sort
  8. CUDA Merge sort

Requirements

NVIDIA CUDA Toolkit 6.0, NVCC v6.0.1, GCC and G++

Follow these instructions to set up your environment: prosciens’s tutorial to set up CUDA 6 compiler environment on Debian testing/sid

Our CUDA sorting code requires devices with CUDA compute capability 3.5 or higher, in order to use the Dinamic Parallelism technology, read more about it here:

NVIDIA blog describing Dinamic Parallelism in Kepler GPUs

Compiling

Run the MAKEFILE

Instructions

To run the program, type:

./a.out-a$algorithm-n$number_of_elements-s$state [-P]

Parameters

  1. -a sorting algorithm
  1. -n number of elements
  2. -s array state
  3. -P print results
ParamValue
-aselection
insertion
shell
quick
heap
merge
gpuquick
gpumerge
-nint > 0
-srandom
ascending
descending
almost
-P

Tested

CUDA code tested on a GeForce GT 740M

GeForce GT 740MFeatures
CUDA Driver Version / Runtime Version6.5 / 6.0
CUDA Capability Major/Minor version number:3.5
Total amount of global memory:2048 MBytes (2147352576 bytes)
( 2) Multiprocessors, (192) CUDA Cores/MP:384 CUDA Cores

About

Repository of sort algorithms in C and CUDA

Resources

Readme
Activity

Stars

34 stars

Watchers

4 watching

Forks

16 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
Repository files navigation
sort
Repository of sorting algorithms in C and CUDA.
Information
Our program generates and fills arrays in four different ways:
  1. arrays with totally random elements
  2. arrays already ordered
  3. arrays ordered in descending order
  4. arrays 90% ordered.
Sorting methods implemented
  1. Selection sort
  2. Insertion sort
  3. Shell sort
  4. Quick sort
  5. Heap sort
  6. Merge sort
  7. CUDA Quick sort
  8. CUDA Merge sort
Requirements
NVIDIA CUDA Toolkit 6.0, NVCC v6.0.1, GCC and G++
Follow these instructions to set up your environment:
prosciens’s tutorial to set up CUDA 6 compiler environment on Debian testing/sid
Our CUDA sorting code requires devices with CUDA compute capability 3.5 or higher, in order to use
the Dinamic Parallelism technology, read more about it here:
NVIDIA blog describing Dinamic Parallelism in Kepler GPUs
Compiling
Run the MAKEFILE
Instructions
To run the program, type:
./a.out-a$algorithm-n$number_of_elements-s$state [-P]
Parameters
  1. -a sorting algorithm
  1. -n number of elements
  2. -s array state
  3. -P print results
ParamValue
-aselection
insertion
shell
quick
heap
merge
gpuquick
gpumerge
-nint > 0
-srandom
ascending
descending
almost
-P
Tested
CUDA code tested on a GeForce GT 740M
GeForce GT 740MFeatures
CUDA Driver Version / Runtime Version6.5 / 6.0
CUDA Capability Major/Minor version number:3.5
Total amount of global memory:2048 MBytes (2147352576 bytes)
( 2) Multiprocessors, (192) CUDA Cores/MP:384 CUDA Cores
About
Repository of sort algorithms in C and CUDA
Resources
Readme
Activity
Stars
34 stars
Watchers
4 watching
Forks
16 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
Repository files navigation
sort
Repository of sorting algorithms in C and CUDA.
Information
Our program generates and fills arrays in four different ways:
  1. arrays with totally random elements
  2. arrays already ordered
  3. arrays ordered in descending order
  4. arrays 90% ordered.
Sorting methods implemented
  1. Selection sort
  2. Insertion sort
  3. Shell sort
  4. Quick sort
  5. Heap sort
  6. Merge sort
  7. CUDA Quick sort
  8. CUDA Merge sort
Requirements
NVIDIA CUDA Toolkit 6.0, NVCC v6.0.1, GCC and G++
Follow these instructions to set up your environment:
prosciens’s tutorial to set up CUDA 6 compiler environment on Debian testing/sid
Our CUDA sorting code requires devices with CUDA compute capability 3.5 or higher, in order to use
the Dinamic Parallelism technology, read more about it here:
NVIDIA blog describing Dinamic Parallelism in Kepler GPUs
Compiling
Run the MAKEFILE
Instructions
To run the program, type:
./a.out-a$algorithm-n$number_of_elements-s$state [-P]
Parameters
  1. -a sorting algorithm
  1. -n number of elements
  2. -s array state
  3. -P print results
ParamValue
-aselection
insertion
shell
quick
heap
merge
gpuquick
gpumerge
-nint > 0
-srandom
ascending
descending
almost
-P
Tested
CUDA code tested on a GeForce GT 740M
GeForce GT 740MFeatures
CUDA Driver Version / Runtime Version6.5 / 6.0
CUDA Capability Major/Minor version number:3.5
Total amount of global memory:2048 MBytes (2147352576 bytes)
( 2) Multiprocessors, (192) CUDA Cores/MP:384 CUDA Cores
About
Repository of sort algorithms in C and CUDA
Resources
Readme
Activity
Stars
34 stars
Watchers
4 watching
Forks
16 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
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sort
Repository of sorting algorithms in C and CUDA.
Information
Our program generates and fills arrays in four different ways:
  1. arrays with totally random elements
  2. arrays already ordered
  3. arrays ordered in descending order
  4. arrays 90% ordered.
Sorting methods implemented
  1. Selection sort
  2. Insertion sort
  3. Shell sort
  4. Quick sort
  5. Heap sort
  6. Merge sort
  7. CUDA Quick sort
  8. CUDA Merge sort
Requirements
NVIDIA CUDA Toolkit 6.0, NVCC v6.0.1, GCC and G++
Follow these instructions to set up your environment:
prosciens’s tutorial to set up CUDA 6 compiler environment on Debian testing/sid
Our CUDA sorting code requires devices with CUDA compute capability 3.5 or higher, in order to use
the Dinamic Parallelism technology, read more about it here:
NVIDIA blog describing Dinamic Parallelism in Kepler GPUs
Compiling
Run the MAKEFILE
Instructions
To run the program, type:
./a.out-a$algorithm-n$number_of_elements-s$state [-P]
Parameters
  1. -a sorting algorithm
  1. -n number of elements
  2. -s array state
  3. -P print results
ParamValue
-aselection
insertion
shell
quick
heap
merge
gpuquick
gpumerge
-nint > 0
-srandom
ascending
descending
almost
-P
Tested
CUDA code tested on a GeForce GT 740M
GeForce GT 740MFeatures
CUDA Driver Version / Runtime Version6.5 / 6.0
CUDA Capability Major/Minor version number:3.5
Total amount of global memory:2048 MBytes (2147352576 bytes)
( 2) Multiprocessors, (192) CUDA Cores/MP:384 CUDA Cores
About
Repository of sort algorithms in C and CUDA
Resources
Readme
Activity
Stars
34 stars
Watchers
4 watching
Forks
16 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
Repository files navigation
sort
Repository of sorting algorithms in C and CUDA.
Information
Our program generates and fills arrays in four different ways:
  1. arrays with totally random elements
  2. arrays already ordered
  3. arrays ordered in descending order
  4. arrays 90% ordered.
Sorting methods implemented
  1. Selection sort
  2. Insertion sort
  3. Shell sort
  4. Quick sort
  5. Heap sort
  6. Merge sort
  7. CUDA Quick sort
  8. CUDA Merge sort
Requirements
NVIDIA CUDA Toolkit 6.0, NVCC v6.0.1, GCC and G++
Follow these instructions to set up your environment:
prosciens’s tutorial to set up CUDA 6 compiler environment on Debian testing/sid
Our CUDA sorting code requires devices with CUDA compute capability 3.5 or higher, in order to use
the Dinamic Parallelism technology, read more about it here:
NVIDIA blog describing Dinamic Parallelism in Kepler GPUs
Compiling
Run the MAKEFILE
Instructions
To run the program, type:
./a.out-a$algorithm-n$number_of_elements-s$state [-P]
Parameters
  1. -a sorting algorithm
  1. -n number of elements
  2. -s array state
  3. -P print results
ParamValue
-aselection
insertion
shell
quick
heap
merge
gpuquick
gpumerge
-nint > 0
-srandom
ascending
descending
almost
-P
Tested
CUDA code tested on a GeForce GT 740M
GeForce GT 740MFeatures
CUDA Driver Version / Runtime Version6.5 / 6.0
CUDA Capability Major/Minor version number:3.5
Total amount of global memory:2048 MBytes (2147352576 bytes)
( 2) Multiprocessors, (192) CUDA Cores/MP:384 CUDA Cores
About
Repository of sort algorithms in C and CUDA
Resources
Readme
Activity
Stars
34 stars
Watchers
4 watching
Forks
16 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
Repository files navigation
sort
Repository of sorting algorithms in C and CUDA.
Information
Our program generates and fills arrays in four different ways:
  1. arrays with totally random elements
  2. arrays already ordered
  3. arrays ordered in descending order
  4. arrays 90% ordered.
Sorting methods implemented
  1. Selection sort
  2. Insertion sort
  3. Shell sort
  4. Quick sort
  5. Heap sort
  6. Merge sort
  7. CUDA Quick sort
  8. CUDA Merge sort
Requirements
NVIDIA CUDA Toolkit 6.0, NVCC v6.0.1, GCC and G++
Follow these instructions to set up your environment:
prosciens’s tutorial to set up CUDA 6 compiler environment on Debian testing/sid
Our CUDA sorting code requires devices with CUDA compute capability 3.5 or higher, in order to use
the Dinamic Parallelism technology, read more about it here:
NVIDIA blog describing Dinamic Parallelism in Kepler GPUs
Compiling
Run the MAKEFILE
Instructions
To run the program, type:
./a.out-a$algorithm-n$number_of_elements-s$state [-P]
Parameters
  1. -a sorting algorithm
  1. -n number of elements
  2. -s array state
  3. -P print results
ParamValue
-aselection
insertion
shell
quick
heap
merge
gpuquick
gpumerge
-nint > 0
-srandom
ascending
descending
almost
-P
Tested
CUDA code tested on a GeForce GT 740M
GeForce GT 740MFeatures
CUDA Driver Version / Runtime Version6.5 / 6.0
CUDA Capability Major/Minor version number:3.5
Total amount of global memory:2048 MBytes (2147352576 bytes)
( 2) Multiprocessors, (192) CUDA Cores/MP:384 CUDA Cores
About
Repository of sort algorithms in C and CUDA
Resources
Readme
Activity
Stars
34 stars
Watchers
4 watching
Forks
16 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
Repository files navigation
sort
Repository of sorting algorithms in C and CUDA.
Information
Our program generates and fills arrays in four different ways:
  1. arrays with totally random elements
  2. arrays already ordered
  3. arrays ordered in descending order
  4. arrays 90% ordered.
Sorting methods implemented
  1. Selection sort
  2. Insertion sort
  3. Shell sort
  4. Quick sort
  5. Heap sort
  6. Merge sort
  7. CUDA Quick sort
  8. CUDA Merge sort
Requirements
NVIDIA CUDA Toolkit 6.0, NVCC v6.0.1, GCC and G++
Follow these instructions to set up your environment:
prosciens’s tutorial to set up CUDA 6 compiler environment on Debian testing/sid
Our CUDA sorting code requires devices with CUDA compute capability 3.5 or higher, in order to use
the Dinamic Parallelism technology, read more about it here:
NVIDIA blog describing Dinamic Parallelism in Kepler GPUs
Compiling
Run the MAKEFILE
Instructions
To run the program, type:
./a.out-a$algorithm-n$number_of_elements-s$state [-P]
Parameters
  1. -a sorting algorithm
  1. -n number of elements
  2. -s array state
  3. -P print results
ParamValue
-aselection
insertion
shell
quick
heap
merge
gpuquick
gpumerge
-nint > 0
-srandom
ascending
descending
almost
-P
Tested
CUDA code tested on a GeForce GT 740M
GeForce GT 740MFeatures
CUDA Driver Version / Runtime Version6.5 / 6.0
CUDA Capability Major/Minor version number:3.5
Total amount of global memory:2048 MBytes (2147352576 bytes)
( 2) Multiprocessors, (192) CUDA Cores/MP:384 CUDA Cores
About
Repository of sort algorithms in C and CUDA
Resources
Readme
Activity
Stars
34 stars
Watchers
4 watching
Forks
16 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
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sort
Repository of sorting algorithms in C and CUDA.
Information
Our program generates and fills arrays in four different ways:
  1. arrays with totally random elements
  2. arrays already ordered
  3. arrays ordered in descending order
  4. arrays 90% ordered.
Sorting methods implemented
  1. Selection sort
  2. Insertion sort
  3. Shell sort
  4. Quick sort
  5. Heap sort
  6. Merge sort
  7. CUDA Quick sort
  8. CUDA Merge sort
Requirements
NVIDIA CUDA Toolkit 6.0, NVCC v6.0.1, GCC and G++
Follow these instructions to set up your environment:
prosciens’s tutorial to set up CUDA 6 compiler environment on Debian testing/sid
Our CUDA sorting code requires devices with CUDA compute capability 3.5 or higher, in order to use
the Dinamic Parallelism technology, read more about it here:
NVIDIA blog describing Dinamic Parallelism in Kepler GPUs
Compiling
Run the MAKEFILE
Instructions
To run the program, type:
./a.out-a$algorithm-n$number_of_elements-s$state [-P]
Parameters
  1. -a sorting algorithm
  1. -n number of elements
  2. -s array state
  3. -P print results
ParamValue
-aselection
insertion
shell
quick
heap
merge
gpuquick
gpumerge
-nint > 0
-srandom
ascending
descending
almost
-P
Tested
CUDA code tested on a GeForce GT 740M
GeForce GT 740MFeatures
CUDA Driver Version / Runtime Version6.5 / 6.0
CUDA Capability Major/Minor version number:3.5
Total amount of global memory:2048 MBytes (2147352576 bytes)
( 2) Multiprocessors, (192) CUDA Cores/MP:384 CUDA Cores
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Repository of sort algorithms in C and CUDA
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