학술논문

High-Performance Memory Allocation on FPGA With Reduced Internal Fragmentation
Document Type
Periodical
Source
IEEE Access Access, IEEE. 11:66672-66681 2023
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Resource management
Memory management
Hardware
Field programmable gate arrays
Heuristic algorithms
Dynamic scheduling
Registers
Dynamic memory allocator
field programmable gate array (FPGA)
high-performance
internal fragmentation
Language
ISSN
2169-3536
Abstract
In this paper, we present two distinct hardware dynamic memory allocation schemes that are based on the binary buddy system algorithm. Our aim is to mitigate internal fragmentation without impacting the area and performance of the system. The first scheme introduces a parallel design for calculating the addresses of free blocks, which results in a decrease in allocation latency while maintaining acceptable resource utilization. This scheme is particularly well-suited for managing a limited number of minimum allocable units (MAU). On the other hand, the second allocator can handle a large number of MAUs due to its innovative searching mechanism. This allocator exhibits lower resource consumption and operates with an acceptable allocation latency. Furthermore, to decrease internal fragmentation, we develop a novel update mechanism for allocating information data structures in both methods. By employing these two allocator schemes, we can improve the efficiency and resource management of dynamic memory allocation for hardware systems. Experimental results demonstrate that the first and second proposed schemes achieve a minimum allocation speed-up of $\times 2$ and $\times 1.8$ compared to their counterparts. At the same time, they achieve a reduction of at least 78% and %88 in resource utilization, respectively. The results show that the total fragmentation is reduced by at least 14% due to the lower internal fragmentation.