Presentation
csDF: A Double-Float Arithmetic Library for the Cerebras CS-2
DescriptionRecently, there have been attempts to utilize AI accelerators for scientific computing; however, these devices generally lack hardware support for double-precision floating-point arithmetic, which is essential for many scientific applications.
The Cerebras CS-2 system (CS-2) delivers extremely high single-precision performance of 1.06 PFlops/s but does not support native double-precision arithmetic. To overcome this limitation and enable scientific computations requiring double precision, a software-based approach is essential.
We propose csDF, a double-float (DF) arithmetic library for the CS-2 that provides DF numeric types and arithmetic operations. To demonstrate the capability of csDF, we implemented a naive pseudo-double-precision matrix multiplication using DF addition and multiplication, and measured its strong scaling performance. Our result shows 8.09 Tera DF-Flops/s, which shows the feasibility of software-based double-precision arithmetic and enables previously infeasible scientific computations.
The Cerebras CS-2 system (CS-2) delivers extremely high single-precision performance of 1.06 PFlops/s but does not support native double-precision arithmetic. To overcome this limitation and enable scientific computations requiring double precision, a software-based approach is essential.
We propose csDF, a double-float (DF) arithmetic library for the CS-2 that provides DF numeric types and arithmetic operations. To demonstrate the capability of csDF, we implemented a naive pseudo-double-precision matrix multiplication using DF addition and multiplication, and measured its strong scaling performance. Our result shows 8.09 Tera DF-Flops/s, which shows the feasibility of software-based double-precision arithmetic and enables previously infeasible scientific computations.
Event Type
Research and ACM SRC Posters
TimeTuesday, 18 November 20258:00am - 5:00pm CST
LocationSecond Floor Atrium
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