ternary content addressable memory
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Author(s):  
Nguyen Trinh ◽  
Anh Le Thi Kim ◽  
Hung Nguyen ◽  
Linh Tran

<span>Content addressable memory (CAM) and ternary content addressable memory (TCAM) are specialized high-speed memories for data searching. CAM and TCAM have many applications in network routing, packet forwarding and Internet data centers. These types of memories have drawbacks on power dissipation and area. As field-programmable gate array (FPGA) is recently being used for network acceleration applications, the demand to integrate TCAM and CAM on FPGA is increasing. Because most FPGAs do not support native TCAM and CAM hardware, methods of implementing algorithmic TCAM using FPGA resources have been proposed through recent years. Algorithmic TCAM on FPGA have the advantages of FPGAs low power consumption and high intergration scalability. This paper proposes a scaleable algorithmic TCAM design on FPGA. The design uses memory blocks to negate power dissipation issue and data collision to save area. The paper also presents a design of a 256 x 104-bit algorithmic TCAM on Intel FPGA Cyclone V, evaluates the performance and application ability of the design on large scale and in future developments.</span>


Author(s):  
Triet Nguyen ◽  
Kiet Ngo ◽  
Nguyen Trinh ◽  
Bao Bui ◽  
Linh Tran ◽  
...  

<span><span>Ternary content addressable memory (TCAM) is a memory that allows high speed searching for data. Not only it is acknowledged as associative memory/storage but also TCAM can compare input searching content (key) against a collection of accumulated data and return the matching address which compatible with this input search data. SRAM-based TCAM utilizes and allocates blocks RAM to perform application of TCAM on FPGA hardware. This paper presents a design of 480×104 bit SRAM-based TCAM on altera cyclone IV FPGA. Our design achieved lookup rate over 150 millions input search data and update speed at 75 million rules per second. The architecture is configurable, allowing various performance trade-offs to be exploited for different ruleset characteristics</span>.</span>


2021 ◽  
Author(s):  
Yu Qian ◽  
Zhenhao Fan ◽  
Haoran Wang ◽  
Chao Li ◽  
Mohsen Imani ◽  
...  

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