Abstract

Many physical models are characterized by the property that some

In this talk, Sumayah will survey a number of malicious hosting infrastructures for different services and approaches to detecting them. Among them are works on an emerging trend of Bulletproof hosting services reselling infrastructure from lower-end service providers, use of residential proxy as a service to avoid server-side blocking and DNS based hosting infrastructure.

This talk will try to clarify some misconceptions about what digital health (DH) is, and what it should not be.

Computing and communications infrastructures have become commodities that transact huge quantities of data and are pervasively interconnected, inside countries, and worldwide. Modern societies largely depend on them.

Existing RDF engines are designed for specific hardware architectures; porting to a different architecture (e.g., GPUs) entails enormous implementation effort. We explore sparse matrix algebra as an alternative for designing a portable, scalable and efficient RDF engine.

Abstract

The talk will present the integrated data-driven modeling system

Current computing infrastructures are evolving from traditional systems to environments that involve sensors, edge devices, instruments, and high-end  computing power in the cloud and HPC systems. A key aspect is how to describe the applications to be executed in such platforms. Very often these applications are not standalone, but involve a set of sub-applications or steps composing a workflow. The scientists then rely on effective environments to describe their workflows and engines to manage them in complex infrastructures. Refreshments - Brown Bag Lunch will be served.

Materials science is a multidisciplinary field of research with many different scientists and engineers having various backgrounds active in it. The literature landscape consequently is populated currently by a wide range of journals which greatly differ in purpose, scope, quality, and readership. Jos Lenders, Deputy Editor of Advanced Materials, Advanced Functional Materials, and Advanced Optical Materials, will track some of the most important developments and trends in the research field and the Advanced journals program. Last year, Advanced Materials reached an Impact Factor of 21.95 and received over 8,300 submissions – and Advanced Functional Materials over 9,200. Only around 15% of all those papers made it to publication in the journal, and this rate is similar for all other Advanced journals. So, what do editors do to select the very best papers, and what can authors do to optimize their chances of having their manuscripts accepted?

This series of lectures guide students to the preparation and analysis of a well-organized abstract. We will discuss the proper language (tense, voice, and person) for abstract writing, and learn how to meet the purposes of different abstracts. Finally, students will have a chance to compose and evaluate their writing. Topics: Overview of abstract writing; Conference abstract journal abstract; Organization of an abstract; Language conventions of abstract writing; Disciplinary abstract analysis; Frequent mistakes of abstract writing.

Many problems in machine learning rely on statistics and optimization. To solve these problems, new techniques are needed. I will show some of these new techniques through selected machine learning problems I have recently worked on, such as nonconvex stochastic optimization, distributed training, adversarial attack, and generative models.

Designing a secure permissionless distributed ledger that performs on par with centralized payment processors such as Visa is challenging. Most existing distributed ledgers are unable to "scale-out" -- growing total processing capacity with number of participants -- and those that do compromise security or decentralization. This work presents OmniLedger, the first scale-out distributed ledger that can preserve long-term security under permissionless operation. OmniLedger ensures strong correctness and security by using a bias-resistant public randomness protocol to choose large statistically representative shards to process transactions, and by introducing an efficient cross-shard commit protocol to handle transactions affecting multiple shards atomically.

This talk begins with an introduction to quantum chemistry for HPC researchers.  We discuss the main computational kernels, how their performance is limited by various bottlenecks, and algorithms and implementations that improve performance.  One particular kernel is the calculation of the Coulomb matrix.  Whereas the fast multipole method (FMM) can be used to rapidly compute the Coulomb potential for sets of point charges, continuous variants of FMM were developed in the 1990s for sets of charge distributions that arise in quantum chemistry.

This dissertation describes detailed performance engineering and optimization of an unstructured computational aerodynamics software system with irregular memory accesses on a wide variety of multi- and many-core emerging high-performance computing scalable architectures, which are expected to be the building blocks of energy-austere exascale systems, and on which algorithmic- and architecture-oriented optimizations are essential for achieving worthy performance.

In the past years, deep learning methods have achieved unprecedented performance on a broad range of problems in various fields from computer vision to speech recognition. So far research has mainly focused on developing deep learning methods for grid-structured data, while many important applications have to deal with graph-structured data.

Space-time conservation element and solution element (CESE) method is a unique finite-volume-type method for computational fluid dynamics (CFD). This approach has several attractive properties, including: (i) unified treatment of the space and time such that only one step is required to construct high-order schemes; (ii) a highly compact stencil regardless of the order of the accuracy; (iii) easiness of extension to any arbitrary shape of polygonal elements. Since its inception, the CESE method has achieved great success in different areas.