1,165 research outputs found
Client-Vendor Collaboration in Information Technology Development Projects And Its Emerging Outcomes
This study investigates the key dimensions of IT project collaboration and its outcomes. We conceptualized key dimensions of client-vendor collaboration, and its emerging outcomes based on literature reviews. Then, we proposed a new research framework that links IT development processes to IT project client-vendor collaboration which in turn affects the outcomes of IT project. We examined the key dimensions of IT project collaboration and their impacts on project outcomes. We identified four critical IT development processes and technologies that contribute to the development of project collaboration. Our results include: (1) Coordination practices and technologies (such as communication quality and coordination technology) significantly influence the effectiveness of IT development.; (2) IT project collaboration can be conceptualized as consisting of two related but distinct constructs: cooperation structure and joint development; (3) IT development processes jointly influence the formation and the development of IT project collaboration. We also found that knowledge-sharing activities significantly improve the usage level of the iterative requirement generation process. (4) Different collaboration behaviors as indicated by IT project collaboration constructs affect two types of outcomes: project performance outcomes and emerging outcomes. IT project collaboration significantly improve both the emerging outcomes (such as team cultivation and relational outcomes) and performance outcomes (time, schedule and functionality). (5) Trust fully mediates the effect of cooperation structure on performance outcomes; suggesting that common rules and structures cannot directly benefit project performance without members’ believing in those rules and agreements. Through IT project collaboration, IT vendors can achieve not only traditional project outcomes but also emerging outcomes such as team cultivation and client-vendor relationship building. The relationships among IT development processes and technologies, project collaboration, and the outcomes of project collaboration are much more complex and dynamic than what the extant literature has portrayed. Multiple factors jointly influence the processes of IT development. Different patterns of client-vendor collaboration also affect the outcomes of the project, in addition, the trust level between the vendor and the client plays a major role in mediating the relationship between client-vendor collaboration and project performance
Canvas: End-to-End Kernel Architecture Search in Neural Networks
The demands for higher performance and accuracy in neural networks (NNs)
never end. Existing tensor compilation and Neural Architecture Search (NAS)
techniques orthogonally optimize the two goals but actually share many
similarities in their concrete strategies. We exploit such opportunities by
combining the two into one and make a case for Kernel Architecture Search
(KAS). KAS reviews NAS from a system perspective and zooms into a more
fine-grained level to generate neural kernels with both high performance and
good accuracy. To demonstrate the potential of KAS, we build an end-to-end
framework, Canvas, to find high-quality kernels as convolution replacements.
Canvas samples from a rich set of fine-grained primitives to stochastically and
iteratively construct new kernels and evaluate them according to user-specified
constraints. Canvas supports freely adjustable tensor dimension sizes inside
the kernel and uses two levels of solvers to satisfy structural legality and
fully utilize model budgets. The evaluation shows that by replacing standard
convolutions with generated new kernels in common NNs, Canvas achieves average
1.5x speedups compared to the previous state-of-the-art with acceptable
accuracy loss and search efficiency. Canvas verifies the practicability of KAS
by rediscovering many manually designed kernels in the past and producing new
structures that may inspire future machine learning innovations. For source
code and implementation, we open-sourced Canvas at
https://github.com/tsinghua-ideal/Canvas
Blessing of High-Order Dimensionality: from Non-Convex to Convex Optimization for Sensor Network Localization
This paper investigates the Sensor Network Localization (SNL) problem, which
seeks to determine sensor locations based on known anchor locations and
partially given anchors-sensors and sensors-sensors distances. Two primary
methods for solving the SNL problem are analyzed: the low-dimensional method
that directly minimizes a loss function, and the high-dimensional semi-definite
relaxation (SDR) method that reformulates the SNL problem as an SDP
(semi-definite programming) problem. The paper primarily focuses on the
intrinsic non-convexity of the loss function of the low-dimensional method,
which is shown in our main theorem. The SDR method, via second-order dimension
augmentation, is discussed in the context of its ability to transform
non-convex problems into convex ones; while the first-order direct dimension
augmentation fails. Additionally, we will show that more edges don't
necessarily contribute to the better convexity of the loss function. Moreover,
we provide an explanation for the success of the SDR+GD (gradient descent)
method which uses the SDR solution as a warm-start of the minimization of the
loss function by gradient descent. The paper also explores the parallels among
SNL, max-cut, and neural networks in terms of the blessing of high-order
dimension augmentation.Comment: 25 pages, 9 figures. References in arxiv. arXiv:1801.06146,
arXiv:1810.04805, arXiv preprint arXiv:1906.05474, arXiv preprint
arXiv:1801.0614
Collaboration in Agile Software Development: Concept and Dimensions
One of the four values listed in the Agile Manifesto emphasizes customer collaboration over contract negotiation, yet the literature has not explained what constitutes customer collaboration and how to assess it. Little research has examined the nature and dimensions of collaboration in the context of agile software development. Based on a grounded theory methodology and using interview data collected from five software development outsourcing vendors in China, we explore the nature and key underlying dimensions of collaboration in agile software development. Five major dimensions of collaboration emerged from our analysis: mutual benefits, engagement, coordination, communication, and knowledge sharing. In turn, each dimension comprises key subdimensions that provide a comprehensive view of collaboration. By revealing the underlying nature and key dimensions, we provide a conceptual basis for operationalizing collaboration that one can employ in future quantitative studies on agility and other project outcomes. Our study results suggest that collaboration in agile software development is multifaceted and mutually occurring in both directions between the customer and the vendor rather than single dimensional as the term “customer collaboration” in the Agile Manifesto indicates
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