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Measuring the impact of Spectre and Meltdown

Summary

The Spectre and Meltdown flaws in modern microprocessors represent a new class of attacks that have been difficult to mitigate. The mitigations that have been proposed have known performance impacts. The reported magnitude of these impacts varies depending on the industry sector and expected workload characteristics. In this paper, we measure the performance impact on several workloads relevant to HPC systems. We show that the impact can be significant on both synthetic and realistic workloads. We also show that the performance penalties are difficult to avoid even in dedicated systems where security is a lesser concern.
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Summary

The Spectre and Meltdown flaws in modern microprocessors represent a new class of attacks that have been difficult to mitigate. The mitigations that have been proposed have known performance impacts. The reported magnitude of these impacts varies depending on the industry sector and expected workload characteristics. In this paper, we...

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Simulation approach to sensor placement using Unity3D

Summary

3D game simulation engines have demonstrated utility in the areas of training, scientific analysis, and knowledge solicitation. This paper will make the case for the use of 3D game simulation engines in the field of sensor placement optimization. Our study used a series of parallel simulations in the Unity3D simulation framework to answer the questions: how many sensors of various modalities are required and where they should be placed to meet a desired threat detection threshold? The result is a framework that not only answers this sensor placement question, but can be easily expanded to differing optimization criteria as well as answer how a particular configuration responds to differing crowd flows or informed/non-informed adversaries. Additionally, we demonstrate the scalability of this framework by running parallel instances on a supercomputing grid and illustrate the processing speed gained.
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Summary

3D game simulation engines have demonstrated utility in the areas of training, scientific analysis, and knowledge solicitation. This paper will make the case for the use of 3D game simulation engines in the field of sensor placement optimization. Our study used a series of parallel simulations in the Unity3D simulation...

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Neural network topologies for sparse training

Published in:
https://arxiv.org/abs/1809.05242

Summary

The sizes of deep neural networks (DNNs) are rapidly outgrowing the capacity of hardware to store and train them. Research over the past few decades has explored the prospect of sparsifying DNNs before, during, and after training by pruning edges from the underlying topology. The resulting neural network is known as a sparse neural network. More recent work has demonstrated the remarkable result that certain sparse DNNs can train to the same precision as dense DNNs at lower runtime and storage cost. An intriguing class of these sparse DNNs is the X-Nets, which are initialized and trained upon a sparse topology with neither reference to a parent dense DNN nor subsequent pruning. We present an algorithm that deterministically generates sparse DNN topologies that, as a whole, are much more diverse than X-Net topologies, while preserving X-Nets' desired characteristics.
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Summary

The sizes of deep neural networks (DNNs) are rapidly outgrowing the capacity of hardware to store and train them. Research over the past few decades has explored the prospect of sparsifying DNNs before, during, and after training by pruning edges from the underlying topology. The resulting neural network is known...

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Don't even ask: database access control through query control

Summary

This paper presents a vision and description for query control, which is a paradigm for database access control. In this model, individual queries are examined before being executed and are either allowed or denied by a pre-defined policy. Traditional view-based database access control requires the enforcer to view the query, the records, or both. That may present difficulty when the enforcer is not allowed to view database contents or the query itself. This discussion of query control arises from our experience with privacy-preserving encrypted databases, in which no single entity learns both the query and the database contents. Query control is also a good fit for enforcing rules and regulations that are not well-addressed by view-based access control. With the rise of federated database management systems, we believe that new approaches to access control will be increasingly important.
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Summary

This paper presents a vision and description for query control, which is a paradigm for database access control. In this model, individual queries are examined before being executed and are either allowed or denied by a pre-defined policy. Traditional view-based database access control requires the enforcer to view the query...

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Colorization of H&E stained tissue using deep learning

Published in:
40th Int. Conf. of the IEEE Engineering in Medicine and Biology Society, EMBC, 17-21 July 2018.

Summary

Histopathology is a critical tool in the diagnosis and stratification of cancer. Digital Pathology involves the scanning of stained and fixed tissue samples to produce high-resolution images that can be used for computer-aided diagnosis and research. A common challenge in digital pathology related to the quality and characteristics of staining, which can vary widely from center to center and also within the same institution depending on the age of the stain and other human factors. In this paper we examine the use of deep learning models for colorizing H&E stained tissue images and compare the results with traditional image processing/statistical approaches that have been developed for standardizing or normalizing histopathology images. We adapt existing deep learning models that have been developed for colorizing natural images and compare the results with models developed specifically for digital pathology. Our results show that deep learning approaches can standardize the colorization of H&E images. The performance as measured by the chi-square statistic shows that the deep learning approach can be nearly as good as current state-of-the art normalization methods.
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Summary

Histopathology is a critical tool in the diagnosis and stratification of cancer. Digital Pathology involves the scanning of stained and fixed tissue samples to produce high-resolution images that can be used for computer-aided diagnosis and research. A common challenge in digital pathology related to the quality and characteristics of staining...

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Mission assurance: beyond secure processing

Published in:
18th IEEE Int. Conf. on Software Quality, Reliability, and Security, QRS 2018, 16-20 July 2018, pp. 593-8.

Summary

The processor of a drone runs essential functions of sensing, communications, coordination, and control. This is the conventional view. But in today's cyber environment, the processor must also provide security to assure mission completion. We have been developing a secure processing architecture for mission assurance. A study on state-of-the-art secure processing technologies has revealed that no one-size-fits-all solution can fully meet our requirements. In fact, we have concluded that the provision of a secure processor as a mission assurance foundation must be holistic and should be approached from a systems perspective. We have thus applied a systems analysis approach to create a secure base for the system. This paper describes our journey of adapting and synergizing various secure processing technologies into a baseline asymmetric multicore processing architecture. We will also describe a functional and security co-design environment, created to customize and optimize the architecture in a design space consisting of hardware, software, performance, and assurance.
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Summary

The processor of a drone runs essential functions of sensing, communications, coordination, and control. This is the conventional view. But in today's cyber environment, the processor must also provide security to assure mission completion. We have been developing a secure processing architecture for mission assurance. A study on state-of-the-art secure...

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Curator: provenance management for modern distributed systems

Published in:
10th Intl. Workshop on Theory and Practice of Provenance, TaPP, 11-12 July 2018.

Summary

Data provenance is a valuable tool for protecting and troubleshooting distributed systems. Careful design of the provenance components reduces the impact on the design, implementation, and operation of the distributed system. In this paper, we present Curator, a provenance management toolkit that can be easily integrated with microservice-based systems and other modern distributed systems. This paper describes the design of Curator and discusses how we have used Curator to add provenance to distributed systems. We find that our approach results in no changes to the design of these distributed systems and minimal additional code and dependencies to manage. In addition, Curator uses the same scalable infrastructure as the distributed system and can therefore scale with the distributed system.
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Summary

Data provenance is a valuable tool for protecting and troubleshooting distributed systems. Careful design of the provenance components reduces the impact on the design, implementation, and operation of the distributed system. In this paper, we present Curator, a provenance management toolkit that can be easily integrated with microservice-based systems and...

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A secure cloud with minimal provider trust

Summary

Bolted is a new architecture for a bare metal cloud with the goal of providing security-sensitive customers of a cloud the same level of security and control that they can obtain in their own private data centers. It allows tenants to elastically allocate secure resources within a cloud while being protected from other previous, current, and future tenants of the cloud. The provisioning of a new server to a tenant isolates a bare metal server, only allowing it to communicate with other tenant's servers once its critical firmware and software have been attested to the tenant. Tenants, rather than the provider, control the tradeoffs between security, price, and performance. A prototype demonstrates scalable end-to-end security with small overhead compared to a less secure alternative.
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Summary

Bolted is a new architecture for a bare metal cloud with the goal of providing security-sensitive customers of a cloud the same level of security and control that they can obtain in their own private data centers. It allows tenants to elastically allocate secure resources within a cloud while being...

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Lessons learned from a decade of providing interactive, on-demand high performance computing to scientists and engineers

Summary

For decades, the use of HPC systems was limited to those in the physical sciences who had mastered their domain in conjunction with a deep understanding of HPC architectures and algorithms. During these same decades, consumer computing device advances produced tablets and smartphones that allow millions of children to interactively develop and share code projects across the globe. As the HPC community faces the challenges associated with guiding researchers from disciplines using high productivity interactive tools to effective use of HPC systems, it seems appropriate to revisit the assumptions surrounding the necessary skills required for access to large computational systems. For over a decade, MIT Lincoln Laboratory has been supporting interactive, on demand high performance computing by seamlessly integrating familiar high productivity tools to provide users with an increased number of design turns, rapid prototyping capability, and faster time to insight. In this paper, we discuss the lessons learned while supporting interactive, on-demand high performance computing from the perspectives of the users and the team supporting the users and the system. Building on these lessons, we present an overview of current needs and the technical solutions we are building to lower the barrier to entry for new users from the humanities, social, and biological sciences.
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Summary

For decades, the use of HPC systems was limited to those in the physical sciences who had mastered their domain in conjunction with a deep understanding of HPC architectures and algorithms. During these same decades, consumer computing device advances produced tablets and smartphones that allow millions of children to interactively...

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On large-scale graph generation with validation of diverse triangle statistics at edges and vertices

Published in:
2018 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW, 21 May 2018.

Summary

Researchers developing implementations of distributed graph analytic algorithms require graph generators that yield graphs sharing the challenging characteristics of real-world graphs (small-world, scale-free, heavy-tailed degree distribution) with efficiently calculable ground-truth solutions to the desired output. Reproducibility for current generators used in benchmarking are somewhat lacking in this respect due to their randomness: the output of a desired graph analytic can only be compared to expected values and not exact ground truth. Nonstochastic Kronecker product graphs meet these design criteria for several graph analytics. Here we show that many flavors of triangle participation can be cheaply calculated while generating a Kronecker product graph.
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Summary

Researchers developing implementations of distributed graph analytic algorithms require graph generators that yield graphs sharing the challenging characteristics of real-world graphs (small-world, scale-free, heavy-tailed degree distribution) with efficiently calculable ground-truth solutions to the desired output. Reproducibility for current generators used in benchmarking are somewhat lacking in this respect due to...

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