Hardware Accelerators for Cloud Computing: Features and Implementation

Date

2021-01-01

Author

Tirlioglu, Anil
Demir, Omer Bayram
Yazar, Alper
Schmidt, Şenan Ece

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

194
views

0
downloads

In this paper, hardware accelerator (FHA) applications realized on FPGA that can be offered as a service in cloud computing systems are discussed. It is necessary to know the hardware resources used by FHA applications and the performance they provide for the efficient meeting of the user requests and effective resource planning. To this end, the first contribution of this paper is to provide a compilation of the literature on the features of frequently used hardware accelerators (matrix multiplication, face detection, FFT) in the last three years, based on common parameters and metrics. The numerical values we provide can be used for cloud resource allocation and creation of sample cloud workloads. The second contribution of our paper is the implementation of the Canny edge detector, a sample hardware accelerator implemented in HLS (High-level Synthesis), using an open source library. In this way, the work flow for the implementation and operation of the hardware accelerator together with its performance are presented.

Subject Keywords

hardware accelerator, Canny edge detection, FPGA, cloud computing

URI

https://hdl.handle.net/11511/100502

DOI

https://doi.org/10.1109/siu53274.2021.9478015

Conference Name

29th IEEE Conference on Signal Processing and Communications Applications (SIU)

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

EXTENSION OF AN OPEN SOURCE RESOURCE MANAGEMENT TOOL FOR HETEROGENEOUS CLOUD DATA CENTERS: IMPLEMENTATION AND EVALUATION Doğan, Taha; Schmidt, Şenan Ece; Department of Electrical and Electronics Engineering (2022-2-11) Cloud Computing is enabled by the virtualization of computing resources to realize users' requests of virtual machines (VMs) and data processing in the scope of Infrastructure as a Service (IaaS) and Software as a Service (SaaS) respectively. The current heterogeneous cloud data centers incorporate hardware accelerators in addition to the conventional servers to offer these services more efficiently. It is an important research problem to allocate heterogeneous physical computing resources to a mixture of ...
CLOUDGEN: Workload generation for the evaluation of cloud computing systems CLOUDGEN: Bulut Bilişim Sistemlerinin Başarim Deǧerlendirmesi icin Iş Yuku Uretimi Koltuk, Furkan; Yazar, Alper; Schmidt, Şenan Ece (2019-04-01) In this paper, we propose CLOUDGEN workflow that produces synthetic workloads for Infrastructure and Platform as a Service for the evaluation of resource management approaches in cloud computing systems. To this end, CLOUDGEN systematically processes and clusters records in a given workload trace and fits distributions for different workload parameters within the clusters. Different than the previous work, clustering is carried out to produce different virtual machine types for achieving models that are sui...
Computational platform for predicting lifetime system reliability profiles for different structure types in a network Akgül, Ferhat (2004-01-01) This paper presents a computational platform for predicting the lifetime system reliability profiles for different structure types located in an existing network. The computational platform has the capability to incorporate time-variant live load and resistance models. Following a review of the theoretical basis, the overall architecture of the computational platform is described. Finally, numerical examples of three existing bridges (i.e., a steel, a prestressed concrete, and a hybrid steel-concrete bridge...
Optimal dynamic resource allocation for heterogenous cloud data centers Ekici, Nazım Umut; Güran Schmidt, Şenan.; Department of Electrical and Electronics Engineering (2019) Today's data centers are mostly cloud-based with virtualized servers to provide on-demand scalability and flexibility of the available resources such as CPU, memory, data storage and network bandwidth. Heterogeneous cloud data centers (CDCs) offer hardware accelerators in addition to these standard cloud server resources. A cloud data center provider may provide Infrastructure as a Service and Platform as a Service (IPaaS), where the user gets a virtual machine (VM) with processing, memory, storage and netw...
A Workflow for Offering Hardware Accelerators as a Cloud Computing Service: Implementation and Evaluation Tırlıoğlu, Anıl; Schmidt, Şenan Ece; Department of Electrical and Electronics Engineering (2022-2) Cloud computing and hardware accelerators are two paradigm changes in the field of information technologies and computers. Accordingly, this thesis proposes a workflow for offering users hardware accelerators implemented on FPGA as computing resources in a heterogeneous cloud data center. To this end, we perform the virtualization of FPGA resources as reconfigurable regions (RRs) and provide these resources through OpenStack, an open-source cloud resource management platform. Our workflow is designed for S...

Citation Formats

A. Tirlioglu, O. B. Demir, A. Yazar, and Ş. E. Schmidt, “Hardware Accelerators for Cloud Computing: Features and Implementation,” presented at the 29th IEEE Conference on Signal Processing and Communications Applications (SIU), ELECTR NETWORK, 2021, Accessed: 00, 2022. [Online]. Available: https://hdl.handle.net/11511/100502.