Publication

FPGAs versus GPUs in Data centers

Babak Falsafi
2017
Journal Articles

Abstract

This article presents position statements and a question-and-answer session by panelists at the Fourth Workshop on Computer Architecture Research Directions. The subject of the debate was the use of field-programmable gate arrays versus GPUs in datacenters.

Official source

Babak Falsafi
2017
Journal Articles

Abstract

Official source

Related concepts (6)

Parallel computing

Parallel computing is a type of computation in which many calculations or processes are carried out simultaneously. Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism. Parallelism has long been employed in high-performance computing, but has gained broader interest due to the physical constraints preventing frequency scaling.

Semiconductor intellectual property core

In electronic design, a semiconductor intellectual property core (SIP core), IP core, or IP block is a reusable unit of logic, cell, or integrated circuit layout design that is the intellectual property of one party. IP cores can be licensed to another party or owned and used by a single party. The term comes from the licensing of the patent or source code copyright that exists in the design. Designers of system on chip (SoC), application-specific integrated circuits (ASIC) and systems of field-programmable gate array (FPGA) logic can use IP cores as building blocks.

Supercomputer

A supercomputer is a computer with a high level of performance as compared to a general-purpose computer. The performance of a supercomputer is commonly measured in floating-point operations per second (FLOPS) instead of million instructions per second (MIPS). Since 2017, there have existed supercomputers which can perform over 1017 FLOPS (a hundred quadrillion FLOPS, 100 petaFLOPS or 100 PFLOPS). For comparison, a desktop computer has performance in the range of hundreds of gigaFLOPS (1011) to tens of teraFLOPS (1013).

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