132 research outputs found
Waks-On/Waks-Off: Fast Oblivious Offline/Online Shuffling and Sorting with Waksman Networks
As more privacy-preserving solutions leverage trusted execution environments (TEEs) like Intel SGX, it becomes pertinent that these solutions can by design thwart TEE side-channel attacks that research has brought to light. In particular, such solutions need to be fully oblivious to circumvent leaking private information through memory or timing side channels.
In this work, we present fast fully oblivious algorithms for shuffling and sorting data. Oblivious shuffling and sorting are two fundamental primitives that are frequently used for permuting data in privacy-preserving solutions. We present novel oblivious shuffling and sorting algorithms in the offline/online model such that the bulk of the computation can be done in an offline phase that is independent of the data to be permuted. The resulting online phase provides performance improvements over state-of-the-art oblivious shuffling and sorting algorithms both asymptotically ( vs. ) and concretely ( and speedups), when permuting items each of size .
Our work revisits Waksman networks, and it uses the key observation that setting the control bits of a Waksman network for a uniformly random shuffle is independent of the data to be shuffled. However, setting the control bits of a Waksman network efficiently and fully obliviously poses a challenge, and we provide a novel algorithm to this end. The total costs (inclusive of offline computation) of our WaksShuffle shuffling algorithm and our WaksSort sorting algorithm are lower than all other fully oblivious shuffling and sorting algorithms when the items are at least moderately sized (i.e., > 1400 B), and the performance gap only widens as the item sizes increase. Furthermore, WaksShuffle improves the online cost of oblivious shuffling by for shuffling items of any size; similarly WaksShuffle+QS, our other sorting algorithm, provides speedups in the online cost of oblivious sorting
Improving low latency applications for reconfigurable devices
This thesis seeks to improve low latency application performance via architectural improvements in reconfigurable devices. This is achieved by improving resource utilisation and access, and by exploiting the different environments within which reconfigurable devices are deployed.
Our first contribution leverages devices deployed at the network level to enable the low latency processing of financial market data feeds. Financial exchanges transmit messages via two identical data feeds to reduce the chance of message loss. We present an approach to arbitrate these redundant feeds at the network level using a Field-Programmable Gate Array (FPGA). With support for any messaging protocol, we evaluate our design using the NASDAQ TotalView-ITCH, OPRA, and ARCA data feed protocols, and provide two simultaneous outputs: one prioritising low latency, and one prioritising high reliability with three dynamically configurable windowing methods.
Our second contribution is a new ring-based architecture for low latency, parallel access to FPGA memory. Traditional FPGA memory is formed by grouping block memories (BRAMs) together and accessing them as a single device. Our architecture accesses these BRAMs independently and in parallel. Targeting memory-based computing, which stores pre-computed function results in memory, we benefit low latency applications that rely on: highly-complex functions; iterative computation; or many parallel accesses to a shared resource. We assess square root, power, trigonometric, and hyperbolic functions within the FPGA, and provide a tool to convert Python functions to our new architecture.
Our third contribution extends the ring-based architecture to support any FPGA processing element. We unify E heterogeneous processing elements within compute pools, with each element implementing the same function, and the pool serving D parallel function calls. Our implementation-agnostic approach supports processing elements with different latencies, implementations, and pipeline lengths, as well as non-deterministic latencies. Compute pools evenly balance access to processing elements across the entire application, and are evaluated by implementing eight different neural network activation functions within an FPGA.Open Acces
Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling
In the last decade, the Industrial Revolution 4.0 brought flexible supply chains and flexible design projects to the forefront. Nevertheless, the recent pandemic, the accompanying economic problems, and the resulting supply problems have further increased the role of logistics and supply chains. Therefore, planning and scheduling procedures that can respond flexibly to changed circumstances have become more valuable both in logistics and projects. There are already several competing criteria of project and logistic process planning and scheduling that need to be reconciled. At the same time, the COVID-19 pandemic has shown that even more emphasis needs to be placed on taking potential risks into account. Flexibility and resilience are emphasized in all decision-making processes, including the scheduling of logistic processes, activities, and projects
Applications
Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications
Perbaikan Internal Blocking Jaringan Interkoneksi Banyak Tingkat Topologi Omega 8x8 dengan Algoritma Look-Ahead
Jaringan interkoneksi banyak tingkat (Multistage Interconnection Network/MIN) hingga saat ini digunakan sebagai switching pada sentral-sentral dalam sistem-sistem Telekomunikasi. Disamping itu MIN juga digunakan sebagai switch penghubung antara prosesor dan modul memori pada sistem-sistem Komputer. Penggunaan MIN semakin diminati karena penghematan jumlah crosspoint yang dimilikinya dibandingkan dengan switch matriks konvensional yang jumlah crosspoint-nya lebih banyak. Selain itu MIN mudah dikontrol dan mampu mendukung koneksi input-output dalam skala besar. Namun MIN bersifat internal blocking, sehingga dibutuhkan suatu cara untuk menjadikannya non-blocking atau mengurangi persentase internal blocking yang dimilikinya. Salah satu cara yang dilakukan untuk maksud tersebut adalah menggunakan algoritma. Pada tulisan ini dibahas algoritma Look-Ahead untuk mengurangi internal blocking MIN topologi Omega 8x8. Dari 2 buah contoh yang dianalisis, untuk permutasi dengan koneksi input-output yang uniform tanpa algoritma Look-Ahead diperoleh hasil bahwa internal blocking sebesar 62,5% dan jika menggunakan algoritma Look-Ahead internal blocking turun menjadi menjadi 25%. Sedangkan dengan permutasi yang memiliki koneksi yang non uniform persentase internal blocking-nya menjadi lebih tinggi yaitu sebesar 87,5% jika tanpa algoritma Look-Ahead, sedangkan dengan algoritma Look-Ahead turun menjadi 50%. Jadi algoritma Look-Ahead sangat mengurangi kegagalan koneksi input-output sebuah permutasi atau dengan kata lain mengurangi internal blocking sebuah jaringan MIN secara signifikan
The Retina in Health and Disease
Vision is the most important sense in higher mammals. The retina is the first step in visual processing and the window to the brain. It is not surprising that problems arising in the retina lead to moderate to severe visual impairments. We offer here a collection of reviews as well as original papers dealing with various aspects of retinal function as well as dysfunction. New approaches in retinal research are described, such as the expression and localization of the endocannabinoid system in the normal retina and the role of cannabinoid receptors that could offer new avenues of research in the development of potential treatments for retinal diseases. Moreover, new insights are offered in advancing knowledge towards the prevention and cure of visual pathologies, mainly AMD, RP, and diabetic retinopathy
Machine Learning for Multi-Layer Open and Disaggregated Optical Networks
L'abstract è presente nell'allegato / the abstract is in the attachmen
Three Risky Decades: A Time for Econophysics?
Our Special Issue we publish at a turning point, which we have not dealt with since World War II. The interconnected long-term global shocks such as the coronavirus pandemic, the war in Ukraine, and catastrophic climate change have imposed significant humanitary, socio-economic, political, and environmental restrictions on the globalization process and all aspects of economic and social life including the existence of individual people. The planet is trappedâthe current situation seems to be the prelude to an apocalypse whose long-term effects we will have for decades. Therefore, it urgently requires a concept of the planet's survival to be builtâonly on this basis can the conditions for its development be created. The Special Issue gives evidence of the state of econophysics before the current situation. Therefore, it can provide excellent econophysics or an inter-and cross-disciplinary starting point of a rational approach to a new era
ABC Transporters in Human Diseases
Mammalian ATP-binding cassette (ABC) transporters constitute a superfamily of proteins involved in many essential cellular processes. Most of these transporters are transmembrane proteins and allow the active transport of solutes, small molecules, and lipids across biological membranes. On the one hand, some of these transporters are involved in drug resistance (also referred to as MDR or multidrug resistance), a process known to be a major brake in most anticancer treatments, and the medical challenge is thus to specifically inhibit their function. On the other hand, molecular defects in some of these ABC transporters are correlated with several rare human diseases, the most well-documented of which being cystic fibrosis, which is caused by genetic variations in ABCC7/CFTR (cystic fibrosis transmembrane conductance regulator). In the latter case, the goal is to rescue the function of the deficient transporters using various means, such as targeted pharmacotherapies and cell or gene therapy. The aim of this Special Issue, âABC Transporters in Human Diseasesâ, is to present, through original articles and reviews, the state-of-the-art of our current knowledge about the role of ABC transporters in human diseases and the proposed therapeutic options based on studies ranging from cell and animal models to patients
- âŚ