Virtually Shared Memory Architectures for Scalable Universal Parallel Computers
Recent results in theoretical computer science confirm that highly parallel, general-purpose shared-memory computers can in principle be built. These results are established by studying emulations of an idealised shared-memory parallel machine model, the Parallel Random Access Machine or PRAM, on realistic distributed-memory parallel systems. Within this context, this paper reports on the basic approaches to provide the common-memory abstraction in a distributed-memory machine (Virtually Shared Memory or VSM).
Understanding the composition of the Internet traffic has many applications nowadays, mainly tracking bandwidth consuming applications, QoS-based traffic engineering and lawful interception of illegal traffic. Although many classification methods such as Support Vector Machines (SVM) have demonstrated their accuracy, not enough attention has been paid to the practical implementation of lightweight classifiers. In this paper, we consider the design of a real-time SVM classifier at many Gbps to allow online detection of categories of applications. Our solution is based on the design of a hardware accelerated SVM classifier on a FPGA board.