ARRANGING MULTICAST FORWARDING TABLE IN CLASS SEQUENCE IN TERNARY-CAM FOR LINE-SPEED LOOKUP

PIM-SM(Protocol Independent Multicast-Sparse Mode) is a main multicast routing pro-tocol in the IPv6(Internet Protocol version 6).It can use either a shared tree or a shortest path tree to deliver data packets,consequently the multicast IP lookup engine requires,in some cases,two searches to get a correct lookup result according to its multicast forwarding rule,and it may result in a new requirement of doubling the lookup speed of the lookup engine.The ordinary method to satisfy this requirement in TCAM(Ternary Content Addressable Memory) based lookup engines is to exploit parallelism among multiple TCAMs.However,traditional parallel methods always induce more re-sources and higher design difficulty.We propose in this paper a novel approach to solve this problem.By arranging multicast forwarding table in class sequence in TCAM and making full use of the intrinsic characteristic of the TCAM,our approach can get the right lookup result with just one search and a single TCAM,while keeping the hardware of lookup engine unchanged.Experimental results have shown that the approach make it possible to satisfy forwarding IPv6 multicast packets at the full link rate of 20 Gb/s with just one TCAM with the current TCAM chip.

IMPROVEMENT OF TCAM-BASED PACKET CLASSIFICATION ALGORITHM

The feature of Ternary Content Addressable Memories(TCAMs) makes them particularly attractive for IP address lookup and packet classification applications in a router system. However,the limitations of TCAMs impede their utilization. In this paper,the solutions for decreasing the power consumption and avoiding entry expansion in range matching are addressed. Experimental results demonstrate that the proposed techniques can make some big improvements on the performance of TCAMs in IP address lookup and packet classification.

A Wire-speed Routing Lookup Algorithm Based on TCAM

An internal structure of Ternary Content Addressable Memory (TCAM) is designed and a Sorting Prefix Block (SPB) algorithm is presented, which is a wire-speed routing lookup algorithm based on TCAM. SPB algorithm makes use of the parallelism of TCAM adequately, and improves the utilization of TCAM by optimum partitions. With the aid of effective management algorithm and memory image, SPB separates critical searching from assistant searching, and improves the searching effect. One performance test indicates that this algorithm can work with different TCAM to meet the requirement of wire-speed routing lookup.

A TCAM-based Two-dimensional Prefix Packet Classification Algorithm

Packet classification (PC) has become the main method to support the quality of service and security of network application. And two-dimeusioual prefix packet classification (PPC) is the popular one. This paper analyzes the problem of ruler conflict, and then presents a TCAM-based two-dimensional PPC algorithm. This algorithm makes use of the parallelism of TCAM to lookup the longest prefix in one instruction cycle. Then it uses a memory image and associated data structures to eliminate the conflicts between rulers, and performs a fast two-dimeusional PPC. Compared with other algorithms, this algorithm has the least time complexity and less space complexity.

Self-selective memristor-enabled in-memory search for highly efficient data mining

Similarity search,that is,finding similar items in massive data,is a fundamental computing problem in many fields such as data mining and information retrieval.However,for large-scale and high-dimension data,it suffers from high computational complexity,requiring tremendous computation resources.Here,based on the low-power self-selective memristors,for the first time,we propose an in-memory search(IMS)system with two innovative designs.First,by exploiting the natural distribution law of the devices resistance,a hardware locality sensitive hashing encoder has been designed to transform the realvalued vectors into more efficient binary codes.Second,a compact memristive ternary content addressable memory is developed to calculate the Hamming distances between the binary codes in parallel.Our IMS system demonstrated a 168energy efficiency improvement over all-transistors counterparts in clustering and classification tasks,while achieving a software-comparable accuracy,thus providing a low-complexity and low-power solution for in-memory data mining applications.

The trend of emerging non-volatile TCAM for parallel search and AI applications

In this paper, we review the recent trends in parallel search and artificial intelligence (AI) applications using emerging non-volatile ternary content addressable memory (TCAM). Firstly, the principle and development of four typical emerging memory used to implement the non-volatile TCAM are discussed. Then, we analyze the principle and challenges of SRAM-based TCAM and non-volatile TCAM for the parallel search. Finally, the research trends and challenges of non-volatile TCAM used for AI application are presented, which include computer-science oriented and neuroscience oriented computing.