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1 The purpose of this research was to create a synergy through combining three domains to assist the designers to choose right communication architecture for the right virtualization technique and to emphasize the importance of using the standard language, + 630 word(s) 630 2020-04-16 11:16:56 |
2 format correct -76 word(s) 554 2020-11-01 10:35:46 |

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Ijaz, Q.; Bourennane, E.; Bashir, A.K.; Asghar, H. FPGAs in Datacenter. Encyclopedia. Available online: (accessed on 09 December 2023).
Ijaz Q, Bourennane E, Bashir AK, Asghar H. FPGAs in Datacenter. Encyclopedia. Available at: Accessed December 09, 2023.
Ijaz, Qaiser, El-Bay Bourennane, Ali Kashif Bashir, Hira Asghar. "FPGAs in Datacenter" Encyclopedia, (accessed December 09, 2023).
Ijaz, Q., Bourennane, E., Bashir, A.K., & Asghar, H.(2020, April 16). FPGAs in Datacenter. In Encyclopedia.
Ijaz, Qaiser, et al. "FPGAs in Datacenter." Encyclopedia. Web. 16 April, 2020.
FPGAs in Datacenter

FPGAs are considered as a competitive computational resource for two reasons, added performance and lower power consumption.

FPGA virtualization datacenters network on chip multi tenancy multi FPGA reconfigurable computing

1. Introduction

Today, datacenters are equipped with the heterogeneous computing resources that range from Central Processing Units (CPUs), Graphical Processing Units (GPUs), Networks on Chip (NoCs) to Field Programmable Gate Arrays (FPGAs), each suited for a certain type of operation, as concluded by Escobar et al. in [1]. They all purvey the scalability and parallelism; hence, unfold new fronts for the existing body of knowledge in algorithmic optimization, computer architecture, microarchitecture, and platform-based design methods [2]. FPGAs are considered as a competitive computational resource for two reasons, added performance and lower power consumption. The cost of electrical power in datacenters is far-reaching, as it contributes roughly half of lifetime cost, as concluded in [3]. This factor alone motivates the companies to deploy FPGAs in datacenters, hence urging the scientific community to exploit High-Performance Reconfigurable Computing (HRC).

2. Application

The applications of FPGAs as computing resource are diverse that includes data analytics, financial computing and cloud computing. This broad range of applications in different areas requires efficient applications and resource management. This lays the foundation for the need of virtualizing the FPGA as a potential resource. Nomenclature is much varying due to the different backgrounds of the researchers contributing to this area. There are many such examples in literature where similar concepts or architecture is described using a different name or term. There is also an abundance of jargon terms and acronyms, which confuse the researchers rather enhancing their understanding. Table 1 identifies and lists non-standard terms in literature from the last decade.

Table 1. Non-Standard Nomenclature Present in Literature.


Non-Standard Term(s) in Published Literature


RAMPSoC in [7]


Lightweight IP (LwIP) in [8]


ASIF (Application Specific FPGA) in [9]


sAES (FPGA based data protection system) in [10]


PFC (FPGA cloud for privacy preserving computation in [11]


CPU-Cache-FPGA in [12]


HwAcc (Hardware accelerators), RIPaaS and RRaaS in [13]


FPGA as a Service (FaaS) and Secure FaaS in [14]


ACCLOUD (Accelerated CLOUD) in [15], FPGAVirt in [16]


vFPGA-based CCMs (Custom Computing Machines) in [17]

This area is stagnated for a lack of a standard nomenclature. We recommend that the scientific community should use a unified nomenclature to present the viewpoint in order to improve the clarity and precision of communication for advancing the knowledge base. We also recommend that this area must be referred as High-Performance Reconfigurable Computing (HRC) in literature. Moreover, it has been observed that the use of computer science language is more conveying as virtualization in FPGAs is comparable to an operating system in CPUs.

We urge the scientific community to come together to develop nomenclature, as it will improve the communication among researchers. It will ease the classification of works for entry-level researchers and help them to focus on complex research problems.

We acknowledge some quality examples such as the suitability of FPGAs has been discussed in depth in the context of high performance computing and heterogenous computing resources in [1], a new classification of FPGA virtualization has been presented in [5], and state of the art has been explored in the context of cloud computing, as defined by the National Institute of Standards and Technology in [18]. These authors have used the standard language of computer science and written in such a way that it added value to the understanding of readers.

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Update Date: 01 Nov 2020