Atomic Add for Double Precision Floating Point???

Accelerated Computing HPC Compilers Legacy PGI Compilers
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I’m currently involved in a project where we study how photon deposits energy in a certain object. That object is a huge 3D matrix and we need to score how much energy (a double precision value) is deposited in each individual element (cube). From programming guide I learned that atomic operation only supports integer. So my question is: Is there any way to solve or circumvent this problem? Or anybody knows when double precision could be supported? Thanks for any suggestion!

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Hi KingCrimson,

I learned that atomic operation only supports integer

CUDA Fortran added support for floating point atomicAdd in July’s 11.7 release. However, it’s only for single precision and requires an NVIDIA compute capable 2.0 device. Unfortunately, I don’t know if/when NVIDIA will add hardware support double precision atomics.

  • Mat
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Thanks for your reply, Mat!

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The decimal keyword denotes a 128-bit data type. Compared to floating-point types, the decimal type has a greater precision and a smaller range, which makes it suitable for financial and monetary calculations. Precision is the main difference where double is a double precision (64 bit) floating point data type and decimal is a 128-bit floating point data type.

Double - 64 bit (15-16 digits)

Decimal - 128 bit (28-29 significant digits)

So Decimals have much higher precision and are usually used within monetary (financial) applications that require a high degree of accuracy. But in performance wise Decimals are slower than double and float types. Double Types are probably the most normally used data type for real values, except handling money. In general, the double type is going to offer at least as great precision and definitely greater speed for arbitrary real numbers. More about…Double vs Decimal

George