A Library of Parallel Algorithms
A Library of Parallel Algorithms This is the toplevel page for accessing code for a collection of parallel algorithms. The algorithms are implemented in the parallel programming language NESL and developed by the Scandal project. For each algorithm we give a brief description along with its complexity (in terms of asymptotic work and parallel depth). In many cases the NESL code is set up so you ca
生物データベース論（並列分散計算フレームワーク）
2015年度先端GPGPUシミュレーション工å¦ç‰¹è«–　第6回　プãƒã‚°ãƒ©ãƒ ã®æ€§èƒ½è©•ä¾¡æŒ‡é‡ï¿½(Flop/Byte，計算律速，メモリ律速)
汎用ソート殺㗠- d.y.d.
00:26 12/12/18 BookLive! 7月ã«å‡ºä¼šã£ã¦ã‹ã‚‰ãšã£ã¨é›»å書ç±ã‚¹ãƒˆã‚¢ã¨ã—㦠BookLive! ã‚’ã²ã„ãã«ã—ã¦ã„ã‚‹ã®ã§ã™ãŒã€ä¸€ä½“ã©ã“ãŒå¥½ããªã®ã‹èªžã‚ŠãŸããªã‚Šã¾ã—ãŸã€‚ ITMedia ã® ã“ã‚Œã§ã‚‚ã†è¿·ã‚ãªã„ã€é›»å書店完全ガイド ã¨ã„ã†ä¸€é€£ã®è¨˜äº‹ã®ã€ é›»å書ç±ã®ç«¯æœ«ã®è©±ã‚ˆã‚Šã‚¹ãƒˆã‚¢ã®è©±ã‚’ã—ã¾ã—ょã†ã‚ˆã¨ã„ã†ã‚³ãƒ³ã‚»ãƒ—トã«æ€ã„ã£ãり影響ã•ã‚Œã¦ã„ã¾ã™ã€‚ ã¨ã„ã£ã¦ã‚‚ã€ç¬¬ä¸€å°è±¡ãŒã€Œæ™®é€šã®ã“ã¨ãŒæ™®é€šã«ã§ãã‚‹ã®ã§æ„Ÿæ¿€ã—ãŸï¼ï¼ã€ã¨ã„ã†ã‚‚ã®ã§ã€ ã¤ã¾ã‚Šä»Šå¹´ã®å‰åŠã«ä½¿ã£ã¦ã„ãŸå¹¾ã¤ã‹ã®é›»å書ç±ã‚¹ãƒˆã‚¢/専用アプリãŒæ®‹å¿µã ã£ãŸã ã‘ã‹ã‚‚ã—ã‚Œã¾ã›ã‚“。 è²·ã£ãŸæœ¬ãŒã©ã“をクリックã™ã‚Œã°èªã‚ã‚‹ã®ã‹ç†è§£ã™ã‚‹ã®ã«10分ã‹ã‹ã£ãŸã€ã¨ã‹ã€ 6冊以上買ã†ã¨æœ¬æ£šã‚¢ãƒ—リã‹ã‚‰ç”»é¢å¤–ã«æœ¬ãŒã¯ã¿å‡ºã‚‹ã®ã§æ‰‹ã§ã„ã¡ã„ã¡æ£šã‚’変ãˆã¦æ•´ç†ã—ãªã„ã¨èªã‚ãªã„ã€ã¨ã‹ã€‚ 本当ã«æ™®é€šã«ä½¿ãˆã‚‹ã¨ã„ã†ä»¥ä¸Šã«ç‰¹ç†ã™ã‚‹ã“ã¨ã‚‚ãªã„ã‚“ã§ã™ãŒã€ ã‚ã€ã§ã‚‚ã€ä»Šå¹´ã«ãªã‚‹
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study top 勉強ã—ãŸäº‹ãƒ»è¦šãˆãŸäº‹ã‚’比較的よã忘れるã®ã§ï¼Œè‡ªåˆ†ã®ãŸã‚ã®è¦šãˆæ›¸ã．主ã«è«–文を実装ã™ã‚‹ä¸Šã§å¿…è¦ãªæ•°å¦ã¨ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ ã‚’ã¾ã¨ã‚ã¦ãŠã．Word -> htmlã®å¤‰æ›ã§ï¼Œãªã‚‹ã¹ãã„ã„方法を探ã—ã¦ã„る途ä¸ãªã®ã§ï¼Œãƒ•ã‚©ãƒ¼ãƒžãƒƒãƒˆãŒå®‰å®šã—ã¾ã›ã‚“...å…ƒã®wordファイルも公開ã—ã¦ãŠã“ã†ã‹... --VisualStudio memo　1 CLAPACKã‚’ã¤ã‹ã† --VisualStudio memo　2 OpenMPã§for文を並列化 --VisualStudio memo　3 CImageã§Jpegã¨ã‹ã‚’よむ --VisualStudio memo　4 Bundlerã§Image based 3D modelingã¨ã‹ --制約付ãドãƒãƒãƒ¼åˆ†å‰² keywords. ドãƒãƒãƒ¼ä¸‰è§’形分割, 制約付ãドãƒãƒãƒ¼åˆ†å‰², é€æ¬¡åŠ 点法 --Mean Shift Clustering
Wikispaces
We are sorry, but the site you are looking for no longer exists Wikispaces was founded in 2005 and has since been used by educators, companies and individuals across the globe. Unfortunately, the time has come where we have had to make the difficult business decision to end the Wikispaces service. We first announced the site closure in January 2018, through a site-wide banner that appeared to all
ã•ã£ããGTAã§DPã®ç·´ç¿’ - Qiita
# !/usr/bin/env runhaskell {-# LANGUAGE NoImplicitPrelude, RecordWildCards #-} {-# OPTIONS -Wall #-} module Main where import Data.Maybe import Data.Tensor.TypeLevel import GTA.Data.JoinList import GTA.Core hiding (items) import NumericPrelude knightMoves :: [Vec2 Int] knightMoves = [Vec :~ x :~ y | x <- [-2..2], y<-[-2..2], x^2 + y^2 == 5] canMoveTo :: Vec2 Int -> Vec2 Int -> Bool canMoveTo a b =
Quick Search algorithm and strstr
The document discusses and benchmarks various string search algorithms, including Quick Search, strstr, and a custom implementation using SSE4.2 instructions. It finds that for short substrings, strstr in GCC utilizing SSE4.2 performs best, while for longer substrings, a modified Quick Search algorithm is faster. The author's own implementation using pcmpestri outperforms all other algorithms, bei
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Hash Function FAQ
I hear a lot of questions and complaints about hash functions in general. Here they are, linked to their standard answers. I'm hashing n things into n buckets, and 1/3 of my buckets are empty, and some buckets have five things in them! What's wrong? What's the best way to structure a hash table? Is this hash designed for character data or numeric data? I've got a scheme where I need to rehash valu
自動微分 ≪フォワード・モード≫ - d.y.d.
23:21 11/12/22 今年èªã‚“ã é¢ç™½ã‚³ãƒ³ãƒ”ュータサイエンス論文紹介カレンダー 第 n (1<n) 週目モードã§ã™ã€‚ ☆ 「難ã—ã„å•é¡Œã€ ☆ 「åã®ãªã„関数〠☆ 「演算ã®ã›ã„ã—ã¤ã€ 「難ã—ã„å•é¡Œã€ [5] R. Impagliazzo and L. A. Levin. "No Better Ways to Generate Hard NP Instances than Picking Uniformly at Random." FOCS 1990. ランダム生æˆã«èˆˆå‘³ãŒã‚ã‚Šã¾ã™ã€‚ パズルゲームを作りã¾ã—ãŸã€‚ ã•ã¦ã€æ‰‹å¼·ã„難易度ã®é¢ãƒ‡ãƒ¼ã‚¿ã‚’ç„¡é™ã«ãƒ©ãƒ³ãƒ€ãƒ 生æˆã™ã‚‹ã«ã¯ã©ã†ã™ã‚Œã°ã„ã„ã ã‚ã†ã€‚ プãƒã‚°ãƒ©ãƒŸãƒ³ã‚°ã‚³ãƒ³ãƒ†ã‚¹ãƒˆã®å•é¡Œã‚’作りã¾ã—ãŸã€‚ ã•ã¦ã€è‡ªå‹•ãƒã‚§ãƒƒã‚¯ç”¨ã®ãƒ†ã‚¹ãƒˆãƒ‡ãƒ¼ã‚¿ã‚’ランダム生æˆã™ã‚‹ã«ã¯ã©ã†ã™ã‚Œã°ã„ã„ã ã‚ã†ã€‚ é©å½“ãªãƒ©ãƒ³ãƒ€ãƒ 生æˆã§ã¯ã€ç°¡å˜ãªã‚±ãƒ¼ã‚¹ã°ã£ã‹ã‚Šä½œã‚‰ã‚Œã¦ã—ã¾ã„ 嘘解法 ã«çª
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Competitive Programming Advent Calendar 3日目ã¯ã€æ•°å¦ã£ã½ã„話をã—ãŸã„ã¨æ€ã„ã¾ã™ã€‚ N以下ã®ç´ æ•°ã‚’ã™ã¹ã¦æ±‚ã‚よ。 N以下ã®ç´ æ•°ã®å€‹æ•°ã‚’求ã‚よ。 A以上B以下ã®ç´ æ•°ã®å€‹æ•°ã‚’求ã‚よ。 ã“ã‚“ãªæ„Ÿã˜ã®å•é¡Œã‚’見ãŸã“ã¨ãŒã‚ã‚‹ã¨æ€ã„ã¾ã™ã€‚ã¾ãŸå•é¡Œã¨ã—ã¦ã§ãªãã¦ã‚‚ã€è§£ãéŽç¨‹ã«ã“ã®ã‚ˆã†ãªã‚µãƒ–å•é¡Œã‚’解ã‹ãªã‘ã‚Œã°ã„ã‘ãªã„å ´åˆã‚‚よãã‚ã‚‹ã¨æ€ã„ã¾ã™ã€‚ç´ æ•°ã«ã¤ã„ã¦ã¯èª¬æ˜Žã—ãªãã¦ã‚‚ã„ã„ã§ã™ã‚ˆã？ ã“ã®ã‚ˆã†ãªå•é¡Œã‚’ç´ æ•°åˆ—æŒ™ã¨å‘¼ã¶ã“ã¨ã«ã—ã¾ã™ã€‚ç´ æ•°åˆ—æŒ™ãŒã§ãã‚Œã°ã€å¤§ãã„æ•°ã®ç´ æ•°åˆ¤å®šã‚„ç´ å› æ•°åˆ†è§£ã‚’ã‚ã£ã¡ã‚ƒé«˜é€ŸåŒ–ã—ãŸã‚Šã€ãƒˆãƒ¼ãƒ†ã‚£ã‚¨ãƒ³ãƒˆé–¢æ•°ã€ãƒ¡ãƒ“ウス関数ç‰ã€æ•°å¦ç³»ã®ã„ã‚ã‚“ãªé–¢æ•°ã‚’求ã‚ãŸã‚Šã§ãã¾ã™ã€‚最近ã®ã‚‚ã®ã§ç´ 数列挙ãŒã»ã¼å¿…é ˆã®ã‚‚ã®ã 㨠Codeforces Beta Round #86 (Div. 1 Only) C. Double Happiness ICPC å›½å†…äºˆé¸ 2011 A
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香å·çœŒé«˜æ¾å¸‚ã«ã¦é–‹å‚¬ã•ã‚ŒãŸALSIP2011(Second Workshop on Algorithms for Large-Scale Information Processing in Knowledge Discovery)ã«å‚åŠ ã—ã¦ããŸã€‚ ç°¡æ½”ãƒ‡ãƒ¼ã‚¿æ§‹é€ ã§æœ‰åãªRajeev Raman先生ã€NIIã®å®šå…¼å…ˆç”Ÿã€PFIã®å²¡é‡ŽåŽŸã•ã‚“ãŒæ‹›å¾…講演をã—ã¦ä¸‹ã•ã‚‹ã¨ã„ã†ã“ã¨ã§ä»¥å‰ã‹ã‚‰æ³¨ç›®ã—ã¦ã„ãŸã€‚ 招待講演ã«åŠ ãˆã¦èˆˆå‘³æ·±ã„10本ã®ç™ºè¡¨ãŒã‚ã‚Šã¨ã¦ã‚‚楽ã—ã‚ãŸã€‚ç§ã®å‹‰å¼·ä¸è¶³ã‚‚ã‚ã£ã¦åˆã‚ã¦çŸ¥ã‚‹ã“ã¨ãŒéžå¸¸ã«å¤šã勉強ã«ãªã£ãŸã€‚ç°¡å˜ã«å†…容をメモã—ã¦ãŠã(ç†è§£ä¸è¶³ã®ãŸã‚é–“é•ã£ãŸã“ã¨ã‚’書ã„ã¦ã„ãŸã‚‰ã™ã¿ã¾ã›ã‚“)。 今回ã®ä¼šè°ã§æœ€ã‚‚興味深ã‹ã£ãŸã®ãŒgrammer-based compressionã¨ã„ã†ã‚‚ã®ã§ã€ã“ã‚Œã¯ä¾‹ãˆã°X=ababã¨ã„ã†æ–‡å—列ãŒã‚ã£ãŸã¨ãã«X1=a,X2=b,X3=X1X2,X=X3X3ã¨ã„ã†æ„Ÿã˜ã§
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The Blog of Scott Aaronson If you take nothing else from this blog: quantum computers won't solve hard problems instantly by just trying all solutions in parallel. Also, please read Zvi Mowshowitz's masterpiece on how to fix K-12 education! For twenty years, the fastest known algorithm to multiply two n-by-n matrices, due to Coppersmith and Winograd, took a leisurely O(n2.376) steps. Â Last year,
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Tree decompositions and large-scale computation
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