title: Ð Ð°ÑÑÐµÑ Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸ÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸ ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÑ ÐÐÐÐ¡ Ð¿ÑÑÐµÐ¼ Ð¾ÑÐµÐ½ÐºÐ¸ FLOPS Ð¸ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ Ð¿Ð¾Ð»ÑÑÐµÐ½Ð½ÑÑ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² Ñ ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÐ¼Ð¸ GPU Ð¸ CPU
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Calculating the performance of modern FPGAs by evaluating FLOPS and comparing the results with modern GPUs and CPUs
Creators: name: ÐÐ¾ÑÐµÑÐºÐ¾Ð², ÐÐ°Ð½Ð¸Ð¸Ð»
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¸ÑÑÐµÐ¼ÑÐµ Ð»Ð¾Ð³Ð¸ÑÐµÑÐºÐ¸Ðµ Ð¸Ð½ÑÐµÐ³ÑÐ°Ð»ÑÐ½ÑÐµ ÑÑ ÐµÐ¼Ñ
Ð¿Ð»Ð°Ð²Ð°ÑÑÐ°Ñ ÑÐ¾ÑÐºÐ°
Ð°ÑÐ¸ÑÐ¼ÐµÑÐ¸ÐºÐ¾-Ð»Ð¾Ð³Ð¸ÑÐµÑÐºÐ¾Ðµ ÑÑÑÑÐ¾Ð¹ÑÑÐ²Ð¾
Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸ÑÐµÐ»ÑÐ½Ð¾ÑÑÑ
Ð·Ð°Ð´ÐµÑÐ¶ÐºÐ°
Ð³Ð»Ð¾Ð±Ð°Ð»ÑÐ½Ð¾Ðµ ÑÐ°ÐºÑÐ¾Ð²Ð¾Ðµ Ð´ÐµÑÐµÐ²Ð¾
ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²Ð¾ Ð¾Ð¿ÐµÑÐ°ÑÐ¸Ð¹ Ð½Ð°Ð´ ÑÐ¸ÑÐ»Ð°Ð¼Ð¸ Ð² ÑÐ¾ÑÐ¼Ð°ÑÐµ Ð¿Ð»Ð°Ð²Ð°ÑÑÐµÐ¹ ÑÐ¾ÑÐºÐ¸ Ð² ÑÐµÐºÑÐ½Ð´Ñ
Xilinx
IP-ÑÐ´ÑÐ¾
ÑÐµÐ½ÑÑÐ°Ð»ÑÐ½ÑÐ¹ Ð¿ÑÐ¾ÑÐµÑÑÐ¾Ñ
Ð³ÑÐ°ÑÐ¸ÑÐµÑÐºÐ¸Ð¹ Ð¿ÑÐ¾ÑÐµÑÑÐ¾Ñ
programmable logic integrated circuits
floating point
arithmetic logic unit
performance
latency
global clock tree
floating point operations per second
IP-core
central processor
graphic processor

description: ÐÐ±ÑÐµÐºÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ â Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð¸ÑÑÐµÐ¼ÑÐµ Ð»Ð¾Ð³Ð¸ÑÐµÑÐºÐ¸Ðµ Ð¸Ð½ÑÐµÐ³ÑÐ°Ð»ÑÐ½ÑÐµ ÑÑÐµÐ¼Ñ. Ð¦ÐµÐ»Ñ ÑÐ°Ð±Ð¾ÑÑ â Ð¿Ð¾Ð»ÑÑÐµÐ½Ð¸Ðµ ÑÐ¸ÑÐ»ÐµÐ½Ð½ÑÑ Ð·Ð½Ð°ÑÐµÐ½Ð¸Ð¹ Ð¾ÑÐµÐ½ÐºÐ¸ Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸-ÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸ Ð² Ð¼ÐµÑÑÐ¸ÐºÐµ ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²Ð° Ð¾Ð¿ÐµÑÐ°ÑÐ¸Ð¹ Ð² ÑÐµÐºÑÐ½Ð´Ñ Ñ ÑÐ¸ÑÐ»Ð°Ð¼Ð¸ Ð² ÑÐ¾ÑÐ¼Ð°ÑÐµ Ð¿Ð»Ð°Ð²Ð°ÑÑÐµÐ¹ ÑÐ¾ÑÐºÐ¸ Ð½ÐµÐºÐ¾ÑÐ¾ÑÑÑ Ð¸Ð· Ð¾ÑÐ½Ð¾Ð²Ð½ÑÑ ÑÐ¸Ð¿Ð¾Ð² ÐºÐ¾Ð¼Ð¿Ð°Ð½Ð¸Ð¸ Xilinx ÑÐ°Ð·Ð½ÑÑ Ð¿Ð¾ÐºÐ¾Ð»ÐµÐ½Ð¸Ð¹. Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ ÑÐ°Ð±Ð¾ÑÑ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð° ÑÐºÐ¾ÑÑÐµÐºÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð½Ð°Ñ Ð¼ÐµÑÐ¾Ð´Ð¸ÐºÐ° ÑÐ°Ñ-ÑÐµÑÐ° Ð¾ÑÐµÐ½ÐºÐ¸ Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸ÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸ ÐÐÐÐ¡ Ð² Ð¼ÐµÑÑÐ¸ÐºÐµ ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²Ð° Ð¾Ð¿ÐµÑÐ°ÑÐ¸Ð¹ Ð² ÑÐµÐºÑÐ½Ð´Ñ Ð½Ð°Ð´ ÑÐ¸ÑÐ»Ð°Ð¼Ð¸ Ð² ÑÐ¾ÑÐ¼Ð°ÑÐµ Ð¿Ð»Ð°Ð²Ð°ÑÑÐµÐ¹ ÑÐ¾ÑÐºÐ¸, Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÑÑÐ°Ñ ÑÑÐ¾ÑÐ½Ð¸ÑÑ Ð¾ÑÐµÐ½ÐºÑ Ð½Ð° 5-17% Ð² Ð·Ð°Ð²Ð¸ÑÐ¸Ð¼Ð¾ÑÑÐ¸ Ð¾Ñ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² ÑÑÐ¼Ð¼Ð°ÑÐ¾ÑÐ¾Ð²/ÑÐ¼Ð½Ð¾Ð¶Ð¸ÑÐµÐ»ÐµÐ¹. ÐÐ¾Ð»ÑÑÐµÐ½Ñ ÑÐ¸ÑÑÑ Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸ÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸ Ð´Ð»Ñ Ð¸ÑÑÐ»ÐµÐ´ÑÐµÐ¼ÑÑ ÐºÑÐ¸ÑÑÐ°Ð»Ð»Ð¾Ð² ÐÐÐÐ¡ Ð¸ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¾ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ Ñ ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÐ¼Ð¸ Ð²ÑÑÐ¸ÑÐ»Ð¸ÑÐµÐ»ÑÐ½ÑÐ¼Ð¸ ÑÑÑÑÐ¾Ð¹ÑÑÐ²Ð°Ð¼Ð¸, ÑÐ°ÐºÐ¸Ð¼Ð¸ ÐºÐ°Ðº CPU ÑÐµÐ¼ÐµÐ¹ÑÑÐ²Ð° i5 Ð¸ GPU ÑÐµÐ¼ÐµÐ¹ÑÑÐ²Ð° GeForce. ÐÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð»Ð¸ÑÑ Ð¾ÑÐºÑÑÑÑÐµ Ð¾Ð±ÑÐ°Ð·Ð¾Ð²Ð°ÑÐµÐ»ÑÐ½ÑÐµ ÑÐµÑÑÑÑÑ Ð¸ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ñ Ð¿Ð¾Ð¸ÑÐºÐ° Ð¸ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¸. ÐÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð»Ð¸ÑÑ ÑÑÐµÐ´ÑÑÐ²Ð° Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð°ÑÐ¸Ð¸ (Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð¹) ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸ Vivado Ð¸ Plan Ahead.
description: The object of research is programmable logic integrated circuits. The purpose of the work is to obtain numerical values of the perfor-mance assessment in the metric of the number of operations per second with numbers in the floating-point format of some of the main Xilinx chips of dif-ferent generations. As a result of the work, an adjusted method for calculating the perfor-mance of FPGAs in the metric of the number of operations per second over numbers in floating point format has been developed, which makes it possible to refine the estimate by 5-17% depending on the parameters of the ad-ders/multipliers. The performance figures for the studied FPGA chips are ob-tained and compared with modern computing devices, such as the i5 family CPU and the GeForce family GPU. Open educational resources and programs for searching and analyzing information were used. Automated development tools Vivado and Plan Ahead were used.