We consider the challenge of black-box optimization within hybrid discrete-continuous and variable-length spaces, a problem that arises in various applications, such as decision tree learning and symbolic regression. We propose DisCo-DSO (Discrete-Continuous Deep Symbolic Optimization), a novel approach that uses a generative model to learn a joint distribution over discrete and continuous design variables to sample new hybrid designs. In contrast to standard decoupled approaches, in which the discrete and continuous variables are optimized separately, our joint optimization approach uses fewer objective function evaluations, is robust against non-differentiable objectives, and learns from prior samples to guide the search, leading to significant improvement in performance and sample efficiency. Our experiments on a diverse set of optimization tasks demonstrate that the advantages of DisCo-DSO become increasingly evident as problem complexity grows. In particular, we illustrate DisCo-DSO's superiority over the state-of-the-art methods for interpretable reinforcement learning with decision trees.

Most implementations of critical Internet protocols are written in type-unsafe languages such as C or C++ and are regularly vulnerable to serious security and reliability problems. Type-safe languages eliminate many errors but are not used to due to the perceived performance overheads.

A SoC, integrating RF/AFE and 1.5 Gb/s SATA PHY, is presented. It supports 471 Mb/s bit-rate at 18xS DVD. A partial parity mode reduces SDRAM bandwidth. A power control mode minimizes system clock rate. The SoC has 10M transistors, occupies 5.4 x 5.1 mm2 in 0.18 mm CMOS process, and consumes 772 mW during 16xS DVD read.

Many software attacks are based on injecting malicious code into a target host. This paper demonstrates the use of a well-known technique, data tainting, to track data received from the network as it propagates through a system and to prevent its execution. Unlike past approaches to taint tracking, which track tainted data by running the system completely in an emulator or simulator, resulting in considerable execution overhead, our work demonstrates the ability to dynamically switch a running system between virtualized and emulated execution. Using this technique, we are able to explore hardware support for taint-based protection that is deployable in real-world situations, as emulation is only used when tainted data is being processed by the CPU. By modifying the CPU, memory, and I/O devices to support taint tracking and protection, we guarantee that data received from the network may not be executed, even if it is written to, and later read from disk. We demonstrate near native speeds for workloads where little taint data is present.

We study the current architecture of the grid and Web services and that of the global information grid (GiG) with the Network Centric Operations and Warfare (NCOW) from the Department of Defense. We compare the GiG core enterprise services with those being developed for Grids (the open grid services architecture) and Web Services (so called WS-* specifications), identifying both similarities and differences. We discuss both modeling and simulation with HLA (high level architecture) and broad defense NCOW applications. We illustrate this analysis with an open geospatial community (OGC) compatible set of geographical information system grid services. We illustrate the use of grids to efficiently support realtime simulation by an application of grids to audio-video conferencing.

Numerous systems have been designed which use virtualization to subdivide the ample resources of a modern computer. Some require specialized hardware, or cannot support commodity operating systems. Some target 100% binary compatibility at the expense of performance. Others sacrifice security or functionality for speed. Few offer resource isolation or performance guarantees; most provide only best-effort provisioning, risking denial of service.This paper presents Xen, an x86 virtual machine monitor which allows multiple commodity operating systems to share conventional hardware in a safe and resource managed fashion, but without sacrificing either performance or functionality. This is achieved by providing an idealized virtual machine abstraction to which operating systems such as Linux, BSD and Windows XP, can be ported with minimal effort.Our design is targeted at hosting up to 100 virtual machine instances simultaneously on a modern server. The virtualization approach taken by Xen is extremely efficient: we allow operating systems such as Linux and Windows XP to be hosted simultaneously for a negligible performance overhead --- at most a few percent compared with the unvirtualized case. We considerably outperform competing commercial and freely available solutions in a range of microbenchmarks and system-wide tests.

A collective communication library for parallel computers includes frequently used operations such as broadcast, reduce, scatter, gather, concatenate, synchronize, and shift. Such a library provides users with a convenient programming interface, efficient communication operations, and the advantage of portability. A library of this nature, the Collective Communication Library (CCL), intended for the line of scalable parallel computer products by IBM, has been designed. CCL is part of the parallel application programming interface of the recently announced IBM 9076 Scalable POWERparallel System 1 (SP1). In this paper, we examine several issues related to the functionality, correctness, and performance of a portable collective communication library while focusing on three novel aspects in the design and implementation of CCL: 1) the introduction of process groups, 2) the definition of semantics that ensures correctness, and 3) the design of new and tunable algorithms based on a realistic point-to-point communication model.>

This paper studies the behavior of scientific applications running on distributed memory parallel computers. Our goal is to quantify the floating point, memory, I/O and communication requirements of highly parallel scientific applications that perform explicit communication. In addition to quantifying these requirements for fixed problem sizes and numbers of processors, we develop analytical models for the effects of changing the problem size and the degree of parallelism for several of the applications. We use the results to evaluate the trade-offs in the design of multicomputer architectures.