TY - CHAP
T1 - Efficient distributed SAT and SAT-based distributed bounded model checking
AU - Ganai, Malay K.
AU - Gupta, Aarti
AU - Yang, Zijiang
AU - Ashar, Pranav
PY - 2003
Y1 - 2003
N2 - SAT-based Bounded Model Checking (BMC), though a robust and scalable verification approach, still is computationally intensive, requiring large memory and time. Interestingly, with the recent development of improved SAT solvers, it is frequently the memory limitation of a single server rather than time that becomes a bottleneck for doing deeper BMC search. Distributing computing requirements of BMC over a network of workstations can overcome the memory limitation of a single server, albeit at increased communication cost. In this paper, we present: a) a method for distributed-SAT over a network of workstations using a Master/Client model where each Client worsktation has an exclusive partition of the SAT problem and uses knowledge of partition topology to communicate with other Clients, b) a method for distributing SAT-based BMC using the distributed-SAT. For the sake of scalability, at no point in the BMC computation does a single workstation have all the information. We experimented on a network of heterogenous workstations interconnected with a standard Ethernet LAN. To illustrate, on an industrial design with -13K FFs and -0.5M gates, the non-disributed BMC on a single workstation (with 4 Gb memory) ran out of memroy after reaching a depth of 120; on the otherhand, our SAT-based distributed BMC over 5 similar workstations was able to go upto 323 steps with a communication overhead of only 30%.
AB - SAT-based Bounded Model Checking (BMC), though a robust and scalable verification approach, still is computationally intensive, requiring large memory and time. Interestingly, with the recent development of improved SAT solvers, it is frequently the memory limitation of a single server rather than time that becomes a bottleneck for doing deeper BMC search. Distributing computing requirements of BMC over a network of workstations can overcome the memory limitation of a single server, albeit at increased communication cost. In this paper, we present: a) a method for distributed-SAT over a network of workstations using a Master/Client model where each Client worsktation has an exclusive partition of the SAT problem and uses knowledge of partition topology to communicate with other Clients, b) a method for distributing SAT-based BMC using the distributed-SAT. For the sake of scalability, at no point in the BMC computation does a single workstation have all the information. We experimented on a network of heterogenous workstations interconnected with a standard Ethernet LAN. To illustrate, on an industrial design with -13K FFs and -0.5M gates, the non-disributed BMC on a single workstation (with 4 Gb memory) ran out of memroy after reaching a depth of 120; on the otherhand, our SAT-based distributed BMC over 5 similar workstations was able to go upto 323 steps with a communication overhead of only 30%.
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U2 - 10.1007/978-3-540-39724-3_30
DO - 10.1007/978-3-540-39724-3_30
M3 - Chapter
AN - SCOPUS:0142214498
SN - 354020363X
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 334
EP - 347
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
A2 - Geist, Daniel
A2 - Tronci, Enrico
PB - Springer Verlag
ER -