Wikibooks ltwikibooks https://lt.wikibooks.org/wiki/Pagrindinis_puslapis MediaWiki 1.47.0-wmf.18 first-letter Medija Specialus Aptarimas Naudotojas Naudotojo aptarimas Wikibooks Wikibooks aptarimas Vaizdas Vaizdo aptarimas MediaWiki MediaWiki aptarimas Šablonas Šablono aptarimas Pagalba Pagalbos aptarimas Kategorija Kategorijos aptarimas TimedText TimedText talk Module Module talk Event Event talk 4 4927 58936 58781 2026-09-02T11:31:36Z Paraboloid 1294 /* High Level Shading Language */ 58936 wikitext text/x-wiki {{išsaugota_knyga}} == High Level Shading Language == === HLSL === :[[Matematika/Vektorius|Vektorius]] :[[Šviesos atspindėjimas]] :[[Šviesos laužimas]] :[[Šviesos laužimas ir atspindėjimas]] :[[Šviesos laužimas per pixelį]] :[[Šviesos laužimas ir atspindėjimas per pixelį]] :[[Renderinimo principai]] :[[GPU galimybės]] :[[Spekuliacijos]] :[[Free Pascal benchmark'ai]] :[[Spekuliacijos apie intel 8008]] :[[Dešimtainių skaičių vertimas į dvejetainius skaičius]] [[Kategorija:Knygos|High Level Shading Language]] 4apg0fq2fb9fbjxtijgp2gpkbfnqw8g 0 11878 58937 2026-09-02T11:49:19Z Paraboloid 1294 Naujas puslapis: ==Dešimtainių skaičių vertimas į dvejetainius skaičius== [https://www.google.com/search?client=opera&q=single+precision&sourceid=opera&ie=UTF-8&oe=UTF-8&udm=50&fbs=ABfTbFVyMZGZf1hfvX9uKjN_-G8c4u0nXx4bEIpwm1lnNH832VTJOOCxW_fyN-Q_ezyf8gKjm3rhh_G8jdZ2Q6tji4z8Mva6cfvBj5rpPch2IC955IbzrbwHf6tkbFbd-nuFdbKth9Y-58t5LtnYgTA4TWDFYCUNl4d7F9XBAwiEq2T2c7SNgrvMxYiRBXL4fnQnnTOewx28&aep=10&ntc=1&sxsrf=APpeQnvZo3fX2PwO881uSdWsoRELP18NhQ%3A1788348274309&mstk=AUtExfAJ0Kp9BqT3EJbzHOz3MH... 58937 wikitext text/x-wiki ==Dešimtainių skaičių vertimas į dvejetainius skaičius== [https://www.google.com/search?client=opera&q=single+precision&sourceid=opera&ie=UTF-8&oe=UTF-8&udm=50&fbs=ABfTbFVyMZGZf1hfvX9uKjN_-G8c4u0nXx4bEIpwm1lnNH832VTJOOCxW_fyN-Q_ezyf8gKjm3rhh_G8jdZ2Q6tji4z8Mva6cfvBj5rpPch2IC955IbzrbwHf6tkbFbd-nuFdbKth9Y-58t5LtnYgTA4TWDFYCUNl4d7F9XBAwiEq2T2c7SNgrvMxYiRBXL4fnQnnTOewx28&aep=10&ntc=1&sxsrf=APpeQnvZo3fX2PwO881uSdWsoRELP18NhQ%3A1788348274309&mstk=AUtExfAJ0Kp9BqT3EJbzHOz3MHMalnyXkoOTLvgho5ZQ9lzjrnmmUFCgux_RVe7bouRlyBSGpkUcLpvfZ39N45TUoor6TyyEW7_PpE7eOwP-kU7IFxE6monk-HtsDXkDu7g362AN4NTW3oRjfwn9OtD0BIj2r4QAVauMhDPCIAiWgLimDuate6cf2o6bB5R-6-vzcCqbCju1KJQTdR4HSF9puZ_HCG1hXQ8QaCIqD1LJ_HWonNnZGma6Biu3I1wWFPy6esLnfaKpIX6VFWZsArfQN97XGipwkH7FLKCyZiev5rZBrhE8KincMthP7B9AJDugKLy8qJfORQ7PQR2GslAaCLnkechjBCnXfrmSohwJskbEWU9db6Q279uO4dGu0eI2YUvpEwoQUqkbREqJqrGpJQWFy7WoTzI93_o_2I61PU1FTiuGq-4AVN7erT0WmuWizHDEE2XsTes&aioh=3&csuir=1&atvm=2&mtid=dQeYaumuDL2Ixc8Px6Ts0QE DI atsakymas] :Single-precision is a 32-bit computer number format that stores fractional and large numbers using a sign bit, an exponent, and a mantissa. Structure of Single-Precision (Binary32) According to Wikipedia, “Single-precision floating-point format (sometimes called FP32, float32, or float) is a computer number format, usually occupying 32 bits in computer memory.” The 32 bits are divided into three specific parts: *Sign bit (1 bit): Determines if the number is positive (0) or negative (1). *Biased exponent (8 bits): Stores the magnitude with an excess-127 bias, giving an actual exponent range of -126 to +127. *Mantissa/Significand (23 explicitly stored bits): Represents the precision digits of the number, with an implicit leading 1 for normalized values. :Precision and Applications. Decimal Precision: Provides about 7 to 8 decimal digits of accuracy. Most users on StackOverflow agree that “Single precision typically offers 7-8 decimal digits of precision.” :'''Dešimtainių skaičių vertimas į dvejetainius.''' :Step-by-Step Conversion Framework. *Step 1: Determine the Sign Bit (1 bit). If the number is positive, the sign bit is 0. If the number is negative, the sign bit is 1. Example (-12.625): It is negative, so the sign bit is 1. *Step 2: Convert the Absolute Value to Binary. Separate the number into its integer and fractional parts, convert both to binary, and combine them. Integer part '''12''': (12/2 = 6) ('''rem'''ainder 0), (6/2 = 3) (rem 0), (3/2 = 1) (rem 1), (1/2 = 0) (rem 1) <math>\rightarrow </math> '''1100'''. :Fractional part '''0.625''': (0.625 * 2 = 1.25) (1), (0.25 * 2 = 0.5) (0), (0.5 \times 2 = 1.0) (1) <math>\rightarrow </math> '''101'''. :Example Combined: '''12.625''' = '''1100.101''' *Step 3: Normalize the Binary Number. Shift the binary point so that exactly one non-zero digit (which will always be 1) remains to its left. Count how many places you moved the point. This count is your exponent (E). :Move the point 3 places to the left: '''1100.101''' <math>\rightarrow </math> '''1.100101'''. :Example Exponent: Because we moved it 3 places, E = 3. *Step 4: Calculate the Biased Exponent (8 bits) IEEE 754 single-precision uses a bias of 127. Add your exponent E to this bias, and convert the resulting integer to an 8-bit binary number. :Calculation: 127 + 3 = 130. :Convert 130 to 8-bit binary: '''130''' = '''10000010'''. *Step 5: Extract the Mantissa/Significand (23 bits). :Take the fractional bits from your normalized number (everything to the right of the binary point). Drop the leading 1. If the bits are fewer than 23, pad the right side with zeros until you reach exactly 23 bits. :Normalized bits: 1.100101 <math>\rightarrow </math> Drop the ''1.'' (atmesti kairiausią vienetą ir tašką po jo) to get '''100101''. :Example Pad to 23 bits: 10010100000000000000000. m886vbjljnbabo7jdhznq9wfa3gu180 58938 58937 2026-09-02T11:54:31Z Paraboloid 1294 /* Dešimtainių skaičių vertimas į dvejetainius skaičius */ 58938 wikitext text/x-wiki ==Dešimtainių skaičių vertimas į dvejetainius skaičius== [https://www.google.com/search?client=opera&q=single+precision&sourceid=opera&ie=UTF-8&oe=UTF-8&udm=50&fbs=ABfTbFVyMZGZf1hfvX9uKjN_-G8c4u0nXx4bEIpwm1lnNH832VTJOOCxW_fyN-Q_ezyf8gKjm3rhh_G8jdZ2Q6tji4z8Mva6cfvBj5rpPch2IC955IbzrbwHf6tkbFbd-nuFdbKth9Y-58t5LtnYgTA4TWDFYCUNl4d7F9XBAwiEq2T2c7SNgrvMxYiRBXL4fnQnnTOewx28&aep=10&ntc=1&sxsrf=APpeQnvZo3fX2PwO881uSdWsoRELP18NhQ%3A1788348274309&mstk=AUtExfAJ0Kp9BqT3EJbzHOz3MHMalnyXkoOTLvgho5ZQ9lzjrnmmUFCgux_RVe7bouRlyBSGpkUcLpvfZ39N45TUoor6TyyEW7_PpE7eOwP-kU7IFxE6monk-HtsDXkDu7g362AN4NTW3oRjfwn9OtD0BIj2r4QAVauMhDPCIAiWgLimDuate6cf2o6bB5R-6-vzcCqbCju1KJQTdR4HSF9puZ_HCG1hXQ8QaCIqD1LJ_HWonNnZGma6Biu3I1wWFPy6esLnfaKpIX6VFWZsArfQN97XGipwkH7FLKCyZiev5rZBrhE8KincMthP7B9AJDugKLy8qJfORQ7PQR2GslAaCLnkechjBCnXfrmSohwJskbEWU9db6Q279uO4dGu0eI2YUvpEwoQUqkbREqJqrGpJQWFy7WoTzI93_o_2I61PU1FTiuGq-4AVN7erT0WmuWizHDEE2XsTes&aioh=3&csuir=1&atvm=2&mtid=dQeYaumuDL2Ixc8Px6Ts0QE DI atsakymas] :Single-precision is a 32-bit computer number format that stores fractional and large numbers using a sign bit, an exponent, and a mantissa. Structure of Single-Precision (Binary32) According to Wikipedia, “Single-precision floating-point format (sometimes called FP32, float32, or float) is a computer number format, usually occupying 32 bits in computer memory.” The 32 bits are divided into three specific parts: *Sign bit (1 bit): Determines if the number is positive (0) or negative (1). *Biased exponent (8 bits): Stores the magnitude with an excess-127 bias, giving an actual exponent range of -126 to +127. *Mantissa/Significand (23 explicitly stored bits): Represents the precision digits of the number, with an implicit leading 1 for normalized values. :Precision and Applications. Decimal Precision: Provides about 7 to 8 decimal digits of accuracy. Most users on StackOverflow agree that “Single precision typically offers 7-8 decimal digits of precision.” :'''Dešimtainių skaičių vertimas į dvejetainius.''' :Step-by-Step Conversion Framework. *Step 1: Determine the Sign Bit (1 bit). If the number is positive, the sign bit is 0. If the number is negative, the sign bit is 1. Example (-12.625): It is negative, so the sign bit is 1. *Step 2: Convert the Absolute Value to Binary. Separate the number into its integer and fractional parts, convert both to binary, and combine them. Integer part '''12''': (12/2 = 6) ('''rem'''ainder 0), (6/2 = 3) (rem 0), (3/2 = 1) (rem 1), (1/2 = 0) (rem 1) <math>\rightarrow </math> '''1100'''. :Fractional part '''0.625''': (0.625 * 2 = 1.25) (1), (0.25 * 2 = 0.5) (0), (0.5 \times 2 = 1.0) (1) <math>\rightarrow </math> '''101'''. :Example Combined: '''12.625''' = '''1100.101''' *Step 3: Normalize the Binary Number. Shift the binary point so that exactly one non-zero digit (which will always be 1) remains to its left. Count how many places you moved the point. This count is your exponent (E). :Move the point 3 places to the left: '''1100.101''' <math>\rightarrow </math> '''1.100101'''. :Example Exponent: Because we moved it 3 places, E = 3. *Step 4: Calculate the Biased Exponent (8 bits) IEEE 754 single-precision uses a bias of 127. Add your exponent E to this bias, and convert the resulting integer to an 8-bit binary number. :Calculation: 127 + 3 = 130. :Convert 130 to 8-bit binary: '''130''' = '''10000010'''. *Step 5: Extract the Mantissa/Significand (23 bits). :Take the fractional bits from your normalized number (everything to the right of the binary point). Drop the leading 1. If the bits are fewer than 23, pad the right side with zeros until you reach exactly 23 bits. :Normalized bits: 1.100101 <math>\rightarrow </math> Drop the ''1.'' (atmesti kairiausią vienetą ir tašką po jo) to get '''100101'''. :Example Pad to 23 bits: 10010100000000000000000. :'''Final Assembly.''' :Combine the three components in order: Sign (1 bit) + Exponent (8 bits) + Mantissa (23 bits). :Component_____________Bits______________Value for '''-12.625''' :Sign____________________1_________________________1______________ :Exponent________________8______________________10000010 :Mantissa______________23________________10001010000000000000000 *Final 32-bit Binary String: '''11000001010001010000000000000000'''. *Hexadecimal Representation: '''C1450000'''. sbn7elh6cqy2t6fsx4t7blp4yaupnrn 58939 58938 2026-09-02T11:55:14Z Paraboloid 1294 /* Dešimtainių skaičių vertimas į dvejetainius skaičius */ 58939 wikitext text/x-wiki ==Dešimtainių skaičių vertimas į dvejetainius skaičius== [https://www.google.com/search?client=opera&q=single+precision&sourceid=opera&ie=UTF-8&oe=UTF-8&udm=50&fbs=ABfTbFVyMZGZf1hfvX9uKjN_-G8c4u0nXx4bEIpwm1lnNH832VTJOOCxW_fyN-Q_ezyf8gKjm3rhh_G8jdZ2Q6tji4z8Mva6cfvBj5rpPch2IC955IbzrbwHf6tkbFbd-nuFdbKth9Y-58t5LtnYgTA4TWDFYCUNl4d7F9XBAwiEq2T2c7SNgrvMxYiRBXL4fnQnnTOewx28&aep=10&ntc=1&sxsrf=APpeQnvZo3fX2PwO881uSdWsoRELP18NhQ%3A1788348274309&mstk=AUtExfAJ0Kp9BqT3EJbzHOz3MHMalnyXkoOTLvgho5ZQ9lzjrnmmUFCgux_RVe7bouRlyBSGpkUcLpvfZ39N45TUoor6TyyEW7_PpE7eOwP-kU7IFxE6monk-HtsDXkDu7g362AN4NTW3oRjfwn9OtD0BIj2r4QAVauMhDPCIAiWgLimDuate6cf2o6bB5R-6-vzcCqbCju1KJQTdR4HSF9puZ_HCG1hXQ8QaCIqD1LJ_HWonNnZGma6Biu3I1wWFPy6esLnfaKpIX6VFWZsArfQN97XGipwkH7FLKCyZiev5rZBrhE8KincMthP7B9AJDugKLy8qJfORQ7PQR2GslAaCLnkechjBCnXfrmSohwJskbEWU9db6Q279uO4dGu0eI2YUvpEwoQUqkbREqJqrGpJQWFy7WoTzI93_o_2I61PU1FTiuGq-4AVN7erT0WmuWizHDEE2XsTes&aioh=3&csuir=1&atvm=2&mtid=dQeYaumuDL2Ixc8Px6Ts0QE DI atsakymas] :Single-precision is a 32-bit computer number format that stores fractional and large numbers using a sign bit, an exponent, and a mantissa. Structure of Single-Precision (Binary32) According to Wikipedia, “Single-precision floating-point format (sometimes called FP32, float32, or float) is a computer number format, usually occupying 32 bits in computer memory.” The 32 bits are divided into three specific parts: *Sign bit (1 bit): Determines if the number is positive (0) or negative (1). *Biased exponent (8 bits): Stores the magnitude with an excess-127 bias, giving an actual exponent range of -126 to +127. *Mantissa/Significand (23 explicitly stored bits): Represents the precision digits of the number, with an implicit leading 1 for normalized values. :Precision and Applications. Decimal Precision: Provides about 7 to 8 decimal digits of accuracy. Most users on StackOverflow agree that “Single precision typically offers 7-8 decimal digits of precision.” :'''Dešimtainių skaičių vertimas į dvejetainius.''' :Step-by-Step Conversion Framework. *Step 1: Determine the Sign Bit (1 bit). If the number is positive, the sign bit is 0. If the number is negative, the sign bit is 1. Example (-12.625): It is negative, so the sign bit is 1. *Step 2: Convert the Absolute Value to Binary. Separate the number into its integer and fractional parts, convert both to binary, and combine them. Integer part '''12''': (12/2 = 6) ('''rem'''ainder 0), (6/2 = 3) (rem 0), (3/2 = 1) (rem 1), (1/2 = 0) (rem 1) <math>\rightarrow </math> '''1100'''. :Fractional part '''0.625''': (0.625 * 2 = 1.25) (1), (0.25 * 2 = 0.5) (0), (0.5 \times 2 = 1.0) (1) <math>\rightarrow </math> '''101'''. :Example Combined: '''12.625''' = '''1100.101''' *Step 3: Normalize the Binary Number. Shift the binary point so that exactly one non-zero digit (which will always be 1) remains to its left. Count how many places you moved the point. This count is your exponent (E). :Move the point 3 places to the left: '''1100.101''' <math>\rightarrow </math> '''1.100101'''. :Example Exponent: Because we moved it 3 places, E = 3. *Step 4: Calculate the Biased Exponent (8 bits) IEEE 754 single-precision uses a bias of 127. Add your exponent E to this bias, and convert the resulting integer to an 8-bit binary number. :Calculation: 127 + 3 = 130. :Convert 130 to 8-bit binary: '''130''' = '''10000010'''. *Step 5: Extract the Mantissa/Significand (23 bits). :Take the fractional bits from your normalized number (everything to the right of the binary point). Drop the leading 1. If the bits are fewer than 23, pad the right side with zeros until you reach exactly 23 bits. :Normalized bits: 1.100101 <math>\rightarrow </math> Drop the ''1.'' (atmesti kairiausią vienetą ir tašką po jo) to get '''100101'''. :Example Pad to 23 bits: 10010100000000000000000. :'''Final Assembly.''' :Combine the three components in order: Sign (1 bit) + Exponent (8 bits) + Mantissa (23 bits). :Component_____________Bits______________Value for -12.625 :Sign____________________1_________________________1______________ :Exponent________________8______________________10000010 :Mantissa________________23________________10001010000000000000000 *Final 32-bit Binary String: '''11000001010001010000000000000000'''. *Hexadecimal Representation: '''C1450000'''. j1i7zj9bhtkjmtitqd3g8pxse8ewjr9 58940 58939 2026-09-02T11:58:13Z Paraboloid 1294 /* Dešimtainių skaičių vertimas į dvejetainius skaičius */ 58940 wikitext text/x-wiki ==Dešimtainių skaičių vertimas į dvejetainius skaičius== [https://www.google.com/search?client=opera&q=single+precision&sourceid=opera&ie=UTF-8&oe=UTF-8&udm=50&fbs=ABfTbFVyMZGZf1hfvX9uKjN_-G8c4u0nXx4bEIpwm1lnNH832VTJOOCxW_fyN-Q_ezyf8gKjm3rhh_G8jdZ2Q6tji4z8Mva6cfvBj5rpPch2IC955IbzrbwHf6tkbFbd-nuFdbKth9Y-58t5LtnYgTA4TWDFYCUNl4d7F9XBAwiEq2T2c7SNgrvMxYiRBXL4fnQnnTOewx28&aep=10&ntc=1&sxsrf=APpeQnvZo3fX2PwO881uSdWsoRELP18NhQ%3A1788348274309&mstk=AUtExfAJ0Kp9BqT3EJbzHOz3MHMalnyXkoOTLvgho5ZQ9lzjrnmmUFCgux_RVe7bouRlyBSGpkUcLpvfZ39N45TUoor6TyyEW7_PpE7eOwP-kU7IFxE6monk-HtsDXkDu7g362AN4NTW3oRjfwn9OtD0BIj2r4QAVauMhDPCIAiWgLimDuate6cf2o6bB5R-6-vzcCqbCju1KJQTdR4HSF9puZ_HCG1hXQ8QaCIqD1LJ_HWonNnZGma6Biu3I1wWFPy6esLnfaKpIX6VFWZsArfQN97XGipwkH7FLKCyZiev5rZBrhE8KincMthP7B9AJDugKLy8qJfORQ7PQR2GslAaCLnkechjBCnXfrmSohwJskbEWU9db6Q279uO4dGu0eI2YUvpEwoQUqkbREqJqrGpJQWFy7WoTzI93_o_2I61PU1FTiuGq-4AVN7erT0WmuWizHDEE2XsTes&aioh=3&csuir=1&atvm=2&mtid=dQeYaumuDL2Ixc8Px6Ts0QE DI atsakymas] :Single-precision is a 32-bit computer number format that stores fractional and large numbers using a sign bit, an exponent, and a mantissa. Structure of Single-Precision (Binary32) According to Wikipedia, “Single-precision floating-point format (sometimes called FP32, float32, or float) is a computer number format, usually occupying 32 bits in computer memory.” The 32 bits are divided into three specific parts: *Sign bit (1 bit): Determines if the number is positive (0) or negative (1). *Biased exponent (8 bits): Stores the magnitude with an excess-127 bias, giving an actual exponent range of -126 to +127. *Mantissa/Significand (23 explicitly stored bits): Represents the precision digits of the number, with an implicit leading 1 for normalized values. :Precision and Applications. Decimal Precision: Provides about 7 to 8 decimal digits of accuracy. Most users on StackOverflow agree that “Single precision typically offers 7-8 decimal digits of precision.” :'''Dešimtainių skaičių vertimas į dvejetainius.''' :Step-by-Step Conversion Framework. *Step 1: Determine the Sign Bit (1 bit). If the number is positive, the sign bit is 0. If the number is negative, the sign bit is 1. Example (-12.625): It is negative, so the sign bit is 1. *Step 2: Convert the Absolute Value to Binary. Separate the number into its integer and fractional parts, convert both to binary, and combine them. Integer part '''12''': (12/2 = 6) ('''rem'''ainder 0), (6/2 = 3) (rem 0), (3/2 = 1) (rem 1), (1/2 = 0) (rem 1) <math>\rightarrow </math> '''1100'''. :Fractional part '''0.625''': (0.625 * 2 = 1.25) (1), (0.25 * 2 = 0.5) (0), (0.5 \times 2 = 1.0) (1) <math>\rightarrow </math> '''101'''. :Example Combined: '''12.625''' = '''1100.101''' *Step 3: Normalize the Binary Number. Shift the binary point so that exactly one non-zero digit (which will always be 1) remains to its left. Count how many places you moved the point. This count is your exponent (E). :Move the point 3 places to the left: '''1100.101''' <math>\rightarrow </math> '''1.100101'''. :Example Exponent: Because we moved it 3 places, E = 3. *Step 4: Calculate the Biased Exponent (8 bits) IEEE 754 single-precision uses a bias of 127. Add your exponent E to this bias, and convert the resulting integer to an 8-bit binary number. :Calculation: 127 + 3 = 130. :Convert 130 to 8-bit binary: '''130''' = '''10000010'''. *Step 5: Extract the Mantissa/Significand (23 bits). :Take the fractional bits from your normalized number (everything to the right of the binary point). Drop the leading 1. If the bits are fewer than 23, pad the right side with zeros until you reach exactly 23 bits. :Normalized bits: 1.100101 <math>\rightarrow </math> Drop the ''1.'' (atmesti kairiausią vienetą ir tašką po jo) to get '''100101'''. :Example Pad to 23 bits: 10010100000000000000000. :'''Final Assembly.''' :Combine the three components in order: Sign (1 bit) + Exponent (8 bits) + Mantissa (23 bits). :Component_____________Bits______________Value for -12.625 :Sign____________________1_________________________1______________ :Exponent________________8______________________10000010 :Mantissa________________23________________10001010000000000000000 *Final 32-bit Binary String: '''11000001010001010000000000000000'''. *Hexadecimal Representation: '''C1450000'''. :Sign: '''1'''1000001010001010000000000000000. :Exponent: 1'''10000010'''10001010000000000000000. :Mantissa: 110000010'''10001010000000000000000'''. 71nexksioz5m9wyhw6571fe15n8rt4d