Browsing by Author "Kumar, V."

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    AlGaN/GaN HEMT-based fully monolithic X-band low noise amplifier
    (Wiley, 2005-04) Schwindt, R.; Kumar, V.; Aktas, O.; Lee, J. W.; Adesida, I.
    A fully monolithic AlGaN/GaN HEMT-based low noise amplifier is reported. The circuit demonstrated a noise figure of 3.5 dB, gain of -7.5 dB, input return loss of -7.5 dB, and output return loss of -15 dB at 8.5 GHz. The dc characteristics of individual 0.25-μm × 150-μm transistors were: maximum current density of 1.0 A/mm, maximum transconductance of 170 mS/mm and a threshold voltage of -6.8 V. The devices have a typical short circuit current gain cutoff frequency of 24.5 GHz and a maximum oscillating frequency of 48 GHz. The devices demonstrated a minimum noise figure of 1.6 dB with an associated gain of 10.6 dB at 10 GHz.
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    Building user-defined runtime adaptation routines for stream processing applications
    (VLDB Endowment, 2012) Jacques-Silva, G.; Gedik, B.; Wagle, R.; Wu, Kun-Lung; Kumar, V.
    Stream processing applications are deployed as continuous queries that run from the time of their submission until their cancellation. This deployment mode limits developers who need their applications to perform runtime adaptation, such as algorithmic adjustments, incremental job deployment, and application-specific failure recovery. Currently, developers do runtime adaptation by using external scripts and/or by inserting operators into the stream processing graph that are unrelated to the data processing logic. In this paper, we describe a component called orchestrator that allows users to write routines for automatically adapting the application to runtime conditions. Developers build an orchestrator by registering and handling events as well as specifying actuations. Events can be generated due to changes in the system state (e.g., application component failures), built-in system metrics (e.g., throughput of a connection), or custom application metrics (e.g., quality score). Once the orchestrator receives an event, users can take adaptation actions by using the orchestrator actuation APIs. We demonstrate the use of the orchestrator in IBM's System S in the context of three different applications, illustrating application adaptation to changes on the incoming data distribution, to application failures, and on-demand dynamic composition. © 2012 VLDB Endowment.
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    CAPSULE: Language and system support for efficient state sharing in distributed stream processing systems
    (ACM, 2012) Losa, G.; Kumar, V.; Andrade, H.; Gedik, Buğra; Hirzel, M.; Soulé, R.; Wu, K. -L.
    Data stream processing applications are often expressed as data flow graphs, composed of operators connected via streams. This structured representation provides a simple yet powerful paradigm for building large-scale, distributed, high-performance applications. However, there are many tasks that require sharing data across operators, and across operators and the runtime using a less structured mechanism than point-to-point data flows. Examples include updating control variables, sending notifications, collecting metrics, building collective models, etc. In this paper we describe CAPSULE, which fills this gap. CAPSULE is a code generation and runtime framework that offers an easy to use and highly flexible framework for developers to realize shared variables (CAPSULE term for shared state) by specifying a data structure (at the programming-language level), and a few associated configuration parameters that qualify the expected usage scenario. Besides the easy of use and flexibility, CAPSULE offers the following important benefits: (1) Custom Code Generation - CAPSULE makes use of user-specified configuration parameters and information from the runtime to generate shared variable servers that are tailored for the specific usage scenario, (2) Composability - CAPSULE supports deployment time composition of the shared variable servers to achieve desired levels of scalability, performance and fault-tolerance, and (3) Extensibility - CAPSULE provides simple interfaces for extending the CAPSULE framework with more protocols, transports, caching mechanisms, etc. We describe the motivation for CAPSULE and its design, report on its implementation status, and then present experimental results. Copyright © 2012 ACM.
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    IBM streams processing language: analyzing big data in motion
    (I B M Corp., 2013-05-17) Hirzel M.; Andrade, H.; Gedik, B.; Jacques-Silva, R.; Khandekar, R.; Kumar, V.; Mendell, M.; Nasgaard, H.; Schneider S.; Soule´, R.; Wu, K. L.
    The IBM Streams Processing Language (SPL) is the programming language for IBM InfoSphere® Streams, a platform for analyzing Big Data in motion. By “Big Data in motion,” we mean continuous data streams at high data-transfer rates. InfoSphere Streams processes such data with both high throughput and short response times. To meet these performance demands, it deploys each application on a cluster of commodity servers. SPL abstracts away the complexity of the distributed system, instead exposing a simple graph-of-operators view to the user. SPL has several innovations relative to prior streaming languages. For performance and code reuse, SPL provides a code-generation interface to C++ and Java®. To facilitate writing well-structured and concise applications, SPL provides higher-order composite operators that modularize stream sub-graphs. Finally, to enable static checking while exposing optimization opportunities, SPL provides a strong type system and user-defined operator models. This paper provides a language overview, describes the implementation including optimizations such as fusion, and explains the rationale behind the language design.
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    Temperature-dependence of a GaN-based HEMT monolithic X-band low noise amplifier
    (IEEE, 2004-10) Schwindt, R. S.; Kumar, V.; Aktaş, Ozan; Lee, J.-W.; Adesida, I.
    The temperature-dependent performance of a fully monolithic AlGaN/GaN HEMT-based X-band low noise amplifier is reported. The circuit demonstrated a noise figure of 3.5 dB, gain of 7.5 dB, input return loss of -7.5 dB, and output return loss of -15 dB at 8.5 GHz at room temperature. The noise figure at 9.5 GHz increased from 2.5 dB at 43°C to 5.0 dB at 150°C. © 2004 IEEE.