1. TransLib: A Library to Explore Transprecision Floating-Point Arithmetic on Multi-Core IoT End-Nodes
- Author
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Mirsalari, Seyed Ahmad, Tagliavini, Giuseppe, Rossi, Davide, and Benini, Luca
- Abstract
Reduced-precision floating-point (FP) arithmetic is being widely adopted to reduce memory footprint and execution time on battery-powered Internet of Things (IoT) end-nodes. However, reduced precision computations must meet end-do-end precision constraints to be acceptable at the application level. This work introduces TransLib11https://github.com/ahmad-mirsalari/TransLib, an open-source kernel library based on transprecision computing principles, which provides knobs to exploit different FP data types (i.e., float, float16, and bfloat16), also considering the trade-off between homogeneous and mixed-precision solutions. We demonstrate the capabilities of the proposed library on PULP, a 32-bit microcontroller (MCU) coupled with a parallel, programmable accelerator. On average, TransLib kernels achieve an IPC of 0.94 and a speed-up of1.64×using 16-bit vectorization. The parallel variants achieve a speed-up of1.97×, 3.91×, and7.59×on 2, 4, and 8 cores, respectively. The memory footprint reduction is between 25% and 50%. Finally, we show that mixed-precision variants increase the accuracy by30×at the cost of2.09×execution time and1.35×memory footprint compared to float16 vectorized.
- Published
- 2023
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