4. The bfloat 16 "brain floating point" format is a 16 bit format used in Google's machine learning and AI software. It is a binary floating point format which is very similar to the single precision IEEE-754 format: 1 bit is allocated for the sign, 8 bits for the exponent with a bias of 127, but only 7 bits are allocated for the fraction (the exponent is always chosen so that the first digit of the mantissa is 1, and then only the fraction is stored in memory). (a) What is the approximate decimal precision of a brain floating point? (b) If the bits are stored in the order: sign, exponent, fraction, and 0 corresponds to a positive sign, then calculate the decimal representation of the number stored as 1 00000110 0100010 (c) Given that the largest exponent actually used for numbers is 11111110, what is the largest number that can be expressed as a bfloat 16?

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
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4.
The bfloat16 "brain floating point" format is a 16 bit format used in
Google's machine learning and AI software. It is a binary floating point format
which is very similar to the single precision IEEE-754 format: 1 bit is allocated for
the sign, 8 bits for the exponent with a bias of 127, but only 7 bits are allocated for
the fraction (the exponent is always chosen so that the first digit of the mantissa is
1, and then only the fraction is stored in memory).
(a) What is the approximate decimal precision of a brain floating point?
(b) If the bits are stored in the order: sign, exponent, fraction, and 0 corresponds to
a positive sign, then calculate the decimal representation of the number stored
as
1 00000110 0100010
(c) Given that the largest exponent actually used for numbers is 11111110, what
is the largest number that can be expressed as a bfloat 16?
(d) Supposing that numbers are truncated (rounded down), what is the maximum
absolute rounding error in bfloat16?
Transcribed Image Text:4. The bfloat16 "brain floating point" format is a 16 bit format used in Google's machine learning and AI software. It is a binary floating point format which is very similar to the single precision IEEE-754 format: 1 bit is allocated for the sign, 8 bits for the exponent with a bias of 127, but only 7 bits are allocated for the fraction (the exponent is always chosen so that the first digit of the mantissa is 1, and then only the fraction is stored in memory). (a) What is the approximate decimal precision of a brain floating point? (b) If the bits are stored in the order: sign, exponent, fraction, and 0 corresponds to a positive sign, then calculate the decimal representation of the number stored as 1 00000110 0100010 (c) Given that the largest exponent actually used for numbers is 11111110, what is the largest number that can be expressed as a bfloat 16? (d) Supposing that numbers are truncated (rounded down), what is the maximum absolute rounding error in bfloat16?
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