Title :
GPEP: Graphics Processing Enhanced Pattern-Matching for High-Performance Deep Packet Inspection
Author :
Vespa, Lucas John ; Weng, Ning
Author_Institution :
Dept. of Comput. Sci., Univ. of Illinois at Springfield, Springfield, IL, USA
Abstract :
Graphics processing units (GPU) can be used to accelerate deep packet inspection. However, the state transition tables used to implement deterministic finite automata are very large and must be stored in DRAM, which inhibits performance and may cause non-deterministic scanning rates. In this work we present GPEP, a GPU-based deep packet inspection engine. GPEP uses an optimized version of our pattern matching algorithm called P3FSM, which has low operational complexity, but reduces the memory requirement such that the state tables can fit into the small on chip memories of a GPU. This allows GPEP to scan quickly and deterministically with no global memory accesses to state tables. We optimize our P3FSM(Portable Predictive Pattern Matching Finite State Machine)algorithm for execution on SIMD devices and to exploit the parallelism of the VLIW arrangement of the GPU processing cores. We show that GPEP consistently achieves over 30 Gb/sdeep packet inspection.
Keywords :
DRAM chips; computational complexity; computer network security; finite state machines; graphics processing units; multiprocessing systems; pattern matching; storage management chips; DRAM; GPEP; GPU processing core; GPU-based deep packet inspection engine; P3FSM algorithm; SIMD device; VLIW arrangement; finite automata; graphics processing enhanced pattern matching algorithm; graphics processing unit; high performance deep packet inspection; memory access; nondeterministic scanning rate; portable predictive pattern matching finite state machine; state transition table; Doped fiber amplifiers; Encoding; Graphics processing unit; Indexes; Inspection; Memory management; Pattern matching;
Conference_Titel :
Internet of Things (iThings/CPSCom), 2011 International Conference on and 4th International Conference on Cyber, Physical and Social Computing
Conference_Location :
Dalian
Print_ISBN :
978-1-4577-1976-9
DOI :
10.1109/iThings/CPSCom.2011.36