Regular Expression Matching with Memristor TCAMs Graves, Catherine E.; Ma, Wen; Sheng, Xia ...
2018 IEEE International Conference on Rebooting Computing (ICRC),
2018-Nov.
Conference Proceeding
Regular expression (RegEx)matching is a key function in network security, where matching of packet data against known malicious signatures filters and alerts against active network intrusions. RegExs ...are widely used in open source and commercial network security systems as they easily and concisely represent complex patterns like those malicious signatures. However, the latency and power required to perform RegEx matching is incredibly high and approaches to this problem struggle to achieve > 1 Gbps on real-world rulesets while internet wirespeeds continue to increase > 100 Gbps. We propose performing RegEx matching using memristor-based ternary content addressable memories (mTCAMs)with compressed finite automata (CFA)to meet this challenge. In this work, we show fabrication of mTCAM circuits with excellent device properties from 100nm to 20nm device sizes and validate mTCAM operation. SPICE simulations investigate mTCAM performance at scale and a mTCAM dynamic power model using 16nm mTCAM layout parameters demonstrates 0.173 fJ/bit/search energy for a 36\times 250 mTCAM array. Using a tiled architecture to implement a Snort ruleset, we estimate performance of our mTCAM approach to be 47.2 Gbps at 1.21W dynamic search power (39 Gbps/W), compared to a state-of-the-art FPGA approach which achieves 3.9 Gbps at 630mW (6.2 Gbps/W). Preliminary error analysis shows the mTCAM approach allows for arbitrarily low false positive/negative rates using minimal and standard state refresh techniques. Dynamic search power is also calculated prior to applying standard TCAM power-reduction techniques capable of lowering power by \sim\times 10 , further demonstrating the promise of mTCAM for wirespeed RegEx matching at low power.
We propose using memristor-based TCAMs (Ternary Content Addressable Memory) to accelerate Regular Expression (RegEx) matching. RegEx matching is a key function in network security, where deep packet ...inspection finds and filters out malicious actors. However, RegEx matching latency and power can be incredibly high and current proposals are challenged to perform wire-speed matching for large scale rulesets. Our approach dramatically decreases RegEx matching operating power, provides high throughput, and the use of mTCAMs enables novel compression techniques to expand ruleset sizes and allows future exploitation of the multi-state (analog) capabilities of memristors. We fabricated and demonstrated nanoscale memristor TCAM cells. SPICE simulations investigate mTCAM performance at scale and a mTCAM power model at 22nm demonstrates 0.2 fJ/bit/search energy for a 36x400 mTCAM. We further propose a tiled architecture which implements a Snort ruleset and assess the application performance. Compared to a state-of-the-art FPGA approach (2 Gbps,~1W), we show x4 throughput (8 Gbps) at 60% the power (0.62W) before applying standard TCAM power-saving techniques. Our performance comparison improves further when striding (searching multiple characters) is considered, resulting in 47.2 Gbps at 1.3W for our approach compared to 3.9 Gbps at 630mW for the strided FPGA NFA, demonstrating a promising path to wire-speed RegEx matching on large scale rulesets.
We propose using memristor-based TCAMs (Ternary Content Addressable Memory) to accelerate Regular Expression (RegEx) matching. RegEx matching is a key function in network security, where deep packet ...inspection finds and filters out malicious actors. However, RegEx matching latency and power can be incredibly high and current proposals are challenged to perform wire-speed matching for large scale rulesets. Our approach dramatically decreases RegEx matching operating power, provides high throughput, and the use of mTCAMs enables novel compression techniques to expand ruleset sizes and allows future exploitation of the multi-state (analog) capabilities of memristors. We fabricated and demonstrated nanoscale memristor TCAM cells. SPICE simulations investigate mTCAM performance at scale and a mTCAM power model at 22nm demonstrates 0.2 fJ/bit/search energy for a 36×400 mTCAM. We further propose a tiled architecture which implements a Snort rule-set and assess the application performance. Compared to a state-of-the-art FPGA approach (2 Gbps, −1W), we show ×4 throughput (8 Gbps) at 60% the power (0.62W) before applying standard TCAM power-saving techniques. Our performance comparison improves further when striding (searching multiple characters) is considered, resulting in 47.2 Gbps at 1.3W for our approach compared to 3.9 Gbps at 630mW for the strided FPGA NFA, demonstrating a promising path to wire-speed RegEx matching on large scale rulesets.
We demonstrate, for the first time, a unique p-i-n diode structure composed of ensembles of unintentionally doped InP nanowires bridging p-type and n-type hydrogenated microcrystalline silicon ...(muc-Si:H) layers on a quartz substrate. Selective area growth was used to restrict nanowires to the perimeter of a circular hole etched into vertically stacked p+ muc-Si:H/SiO 2 /n+ muc-Si:H thin films. DC electrical measurements confirm diode current-voltage characteristics with 25 nA reverse leakage current and an ideality factor of 3.9. Our demonstration suggests that active devices incorporating III-V compound semiconductor nanowires can be integrated onto low cost non- single crystal material platforms.
Indium phosphide nanostructures grown on hydrogenated silicon films are studied. The hydrogenated silicon films were deposited on various metallic and dielectric substrate surfaces, then indium ...phosphide nanostructures were grown on the hydrogenated silicon films. The hydrogenated silicon films and the indium phosphide nanostructures were examined to assess their structural, chemical and optical properties.
