[HTML][HTML] A survey on hardware accelerators: Taxonomy, trends, challenges, and perspectives

B Peccerillo, M Mannino, A Mondelli… - Journal of Systems …, 2022 - Elsevier
In recent years, the limits of the multicore approach emerged in the so-called “dark silicon”
issue and diminishing returns of an ever-increasing core count. Hardware manufacturers …

A survey on optimization techniques for edge artificial intelligence (ai)

C Surianarayanan, JJ Lawrence, PR Chelliah… - Sensors, 2023 - mdpi.com
Artificial Intelligence (Al) models are being produced and used to solve a variety of current
and future business and technical problems. Therefore, AI model engineering processes …

Sara: Scaling a reconfigurable dataflow accelerator

Y Zhang, N Zhang, T Zhao, M Vilim… - 2021 ACM/IEEE 48th …, 2021 - ieeexplore.ieee.org
The need for speed in modern data-intensive work-loads and the rise of" dark silicon" in the
semiconductor industry are pushing for larger, faster, and more energy and area-efficient …

High-level synthesis hardware design for fpga-based accelerators: Models, methodologies, and frameworks

RS Molina, V Gil-Costa, ML Crespo, G Ramponi - IEEE Access, 2022 - ieeexplore.ieee.org
Hardware accelerators based on field programmable gate array (FPGA) and system on chip
(SoC) devices have gained attention in recent years. One of the main reasons is that these …

Democratizing domain-specific computing

Y Chi, W Qiao, A Sohrabizadeh, J Wang… - Communications of the …, 2022 - dl.acm.org
Democratizing Domain-Specific Computing Page 1 GENERAL-PURPOSE COMPUTERS
ARE widely used in our modern society. There were close to 24 million software …

Symphony: Orchestrating sparse and dense tensors with hierarchical heterogeneous processing

M Pellauer, J Clemons, V Balaji, N Crago… - ACM Transactions on …, 2023 - dl.acm.org
Sparse tensor algorithms are becoming widespread, particularly in the domains of deep
learning, graph and data analytics, and scientific computing. Current high-performance …