1,406 research outputs found

    Actors that Unify Threads and Events

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    There is an impedance mismatch between message-passing concurrency and virtual machines, such as the JVM. VMs usually map their threads to heavyweight OS processes. Without a lightweight process abstraction, users are often forced to write parts of concurrent applications in an event-driven style which obscures control flow, and increases the burden on the programmer. In this paper we show how thread-based and event-based programming can be unified under a single actor abstraction. Using advanced abstraction mechanisms of the Scala programming language, we implemented our approach on unmodified JVMs. Our programming model integrates well with the threading model of the underlying VM

    Spaceborne VHSIC multiprocessor system for AI applications

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    A multiprocessor system, under design for space-station applications, makes use of the latest generation symbolic processor and packaging technology. The result will be a compact, space-qualified system two to three orders of magnitude more powerful than present-day symbolic processing systems

    MULTI - a LISP based multiprocessing system

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    Cost effective RISC core supporting the large sending offload

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    The Ethernet speed has increased sending and receiving frames from 40 to 100 Gbps after the IEEE P802.3ba released. The industry and academia have focused scaling up the TCP/IP protocol processing for 40-100 Gbps. LSO is a de facto standard, which is offloaded to network interface for sending packets up to 10 Gbps. It not clears whether a network interface can support such function for new 40-100 Gbps. The widely use of the hardware-based NIC such as the use of a fully customized logic based network interface can be due to the following reasons; Still it is not clear whether the General Purpose Processor (GPP) can provide the processing required for high-speed line beyond the 10 Gbps. Also, the limit of the GPP's clock in supporting the processing of network interfaces. However, using a RISC core engine for offloading the LSO function can deliver some important features to network interfaces design, such as simplicity, scalability, shorter developing cycle time. In this paper, we have investigated using a specialized RISC core to process the LSO functions for TCP/IP and UDP/IP for high-speed communications rate up to 100 Gbps. To achieve this, we have enhanced the LSO algorithm to scale it to 100 Gbps. A fast DMA is used to support transferring data in the network interface. The LSO processing methodology on the network has presented. In addition, the RISC's performance and data movements for high communication rate up to 100 Gbps have been measured. A 148 MHz RISC core can support the sending-side processing for up to 100 Gbps transmission speed for the TCP/IP and UDP/IP protocol when the MTU is applied (1500 bytes). A DMA with 3759 MHz is required to eliminate the idle cycles while transferring data over the 64-bit local bus

    Computation of Electromagnetic Fields Scattered From Objects With Uncertain Shapes Using Multilevel Monte Carlo Method

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    Computational tools for characterizing electromagnetic scattering from objects with uncertain shapes are needed in various applications ranging from remote sensing at microwave frequencies to Raman spectroscopy at optical frequencies. Often, such computational tools use the Monte Carlo (MC) method to sample a parametric space describing geometric uncertainties. For each sample, which corresponds to a realization of the geometry, a deterministic electromagnetic solver computes the scattered fields. However, for an accurate statistical characterization the number of MC samples has to be large. In this work, to address this challenge, the continuation multilevel Monte Carlo (CMLMC) method is used together with a surface integral equation solver. The CMLMC method optimally balances statistical errors due to sampling of the parametric space, and numerical errors due to the discretization of the geometry using a hierarchy of discretizations, from coarse to fine. The number of realizations of finer discretizations can be kept low, with most samples computed on coarser discretizations to minimize computational cost. Consequently, the total execution time is significantly reduced, in comparison to the standard MC scheme.Comment: 25 pages, 10 Figure
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