Off-chip replacement （capacity and conflict） and coherent read misses in a distributed shared memory system cause execution to stall for hundreds of cycles. These off-chip replacement and coherent read misses are recurring and forming sequences of two or more misses called streams. Prior streaming techniques ignored reordering of misses and not-recently-accessed streams while streaming data. In this paper, we present stream prefetcher design that can deal with both problems. Our stream prefetcher design utilizes stream waiting rooms to store not-recently-accessed streams. Stream waiting rooms help remove more off-chip misses. Using trace based simulation% our stream prefetcher design can remove 8% to 66% （on average 40%） and 17% to 63% （on average 39%） replacement and coherent read misses, respectively. Using cycle-accurate full-system simulation, our design gives speedups from 1.00 to 1.17 of princeton application repository for shared-memory computers （PARSEC） workloads running on a distributed shared memory system with the exception of dedup and swaptions workloads.
Traffic classification is critical to effective network management. However, more and more pro- prietary, encrypted, and dynamic protocols make traditional traffic classification methods less effective. A Message and Command Correlation （MCC） method was developed to identify interactive protocols （such as P2P file sharing protocols and Instant Messaging （IM） protocols） by session analyses. Unlike traditional packet-based classification approaches, this method exploits application session information by clustering packets into application messages which are used for further classification. The efficacy and accuracy of the MCC method was evaluated with real world traffic, including P2P file sharing protocols Thunder and Bit- Torrent, and IM protocols QQ and GTalk. The tests show that the false positive rate is less than 3% and the false negative rate is below 8%, and that MCC only needs to check 8.7% of the packets or 0.9% of the traffic. Therefore, this approach has great potential for accurately and quickly discovering new types of interactive application protocols.
