Field programmable gate array applications—A scientometric review

J Ruiz-Rosero, G Ramirez-Gonzalez, R Khanna - Computation, 2019 - mdpi.com
Field Programmable Gate Array (FPGA) is a general purpose programmable logic device
that can be configured by a customer after manufacturing to perform from a simple logic gate …

Heteroflow: An accelerator programming model with decoupled data placement for software-defined fpgas

S **ang, YH Lai, Y Zhou, H Chen, N Zhang… - Proceedings of the …, 2022 - dl.acm.org
To achieve high performance with FPGA-equipped heterogeneous compute systems, it is
crucial to co-optimize data placement and compute scheduling to maximize data reuse and …

Reconfigurable hardware accelerators: Opportunities, trends, and challenges

C Wang, W Lou, L Gong, L **, L Tan, Y Hu, X Li… - arxiv preprint arxiv …, 2017 - arxiv.org
With the emerging big data applications of Machine Learning, Speech Recognition, Artificial
Intelligence, and DNA Sequencing in recent years, computer architecture research …

Scale-out acceleration for machine learning

J Park, H Sharma, D Mahajan, JK Kim, P Olds… - Proceedings of the 50th …, 2017 - dl.acm.org
The growing scale and complexity of Machine Learning (ML) algorithms has resulted in
prevalent use of distributed general-purpose systems. In a rather disjoint effort, the …

Fluid: An asynchronous high-level synthesis tool for complex program structures

R Li, L Berkley, Y Yang… - 2021 27th IEEE …, 2021 - ieeexplore.ieee.org
Current high-level synthesis (HLS) tools that generate synchronous logic construct a state
machine that schedules program operations in each clock cycle. Rather than this centralized …

Heterogeneous architectures for big data batch processing in mapreduce paradigm

M Goudarzi - IEEE Transactions on Big Data, 2017 - ieeexplore.ieee.org
The amount of digital data produced worldwide is exponentially growing. While the source of
this data, collectively known as Big Data, varies from among mobile services to cyber …

A survey of big data machine learning applications optimization in cloud data centers and networks

SH Mohamed, TEH El-Gorashi… - arxiv preprint arxiv …, 2019 - arxiv.org
This survey article reviews the challenges associated with deploying and optimizing big data
applications and machine learning algorithms in cloud data centers and networks. The …

An fpga-based integrated mapreduce accelerator platform

C Kachris, D Diamantopoulos, GC Sirakoulis… - Journal of Signal …, 2017 - Springer
MapReduce is a programming framework for distributed systems that is used to
automatically parallelize and schedule the tasks to distributed resources. MapReduce is …

A study of reconfigurable accelerators for cloud computing

N Mohammedali, MO Agyeman - … of the 2nd International Symposium on …, 2018 - dl.acm.org
Due to the exponential increase in network traffic in the data centers, thousands of servers
interconnected with high bandwidth switches are required. Field Programmable Gate Arrays …

Sorting big data on heterogeneous near-data processing systems

E Vermij, L Fiorin, C Hagleitner, K Bertels - Proceedings of the …, 2017 - dl.acm.org
Big data workloads assumed recently a relevant importance in many business and scientific
applications. Sorting elements efficiently in big data workloads is a key operation. In this …