Imperial College London

Displaying 1-40 of 165 results

  • White Papers // Jun 2014

    Self-Adaptive Containers: Functionality Extensions and Further Case Study

    As the number of execution environments and application contexts rises exponentially, ever-changing non-functional requirements can lead to repeated code refactoring. In addition, scaling up software to support large input sizes may require major modification of code. To address these challenges, the authors have previously proposed a framework of self-adaptive containers...

    Provided By Imperial College London

  • White Papers // Mar 2014

    Separation Logic-Assisted Code Transformations for Efficient High-Level Synthesis

    The capabilities of modern FPGAs permit the mapping of increasingly complex applications into reconfigurable hardware. High-Level Synthesis (HLS) promises a significant shortening of the FPGA design cycle by raising the abstraction level of the design entry to high-level languages such as C/C++. Applications using dynamic, pointer-based data structures and dynamic...

    Provided By Imperial College London

  • White Papers // Mar 2014

    GPU Vs FPGA : A Comparative Analysis for Non-Standard Precision

    FPGAs and GPUs are increasingly used in a range of high performance computing applications. When implementing numerical algorithms on either platform, the authors can choose to represent operands with different levels of accuracy. A trade-off exists between the numerical accuracy of arithmetic operators and the resources needed to implement them....

    Provided By Imperial College London

  • White Papers // Feb 2014

    Learning-Based Optimization of Cache Content in a Small Cell Base Station

    Optimal cache content placement in a wireless small cell Base Station (sBS) with limited backhaul capacity is studied. The sBS has a large cache memory and provides content-level selective offloading by delivering high data rate contents to users in its coverage area. The goal of the sBS Content Controller (CC)...

    Provided By Imperial College London

  • White Papers // Jan 2014

    Simulation and Modelling of RAID 0 System Performance

    RAID systems are fundamental components of modern storage infrastructures. It is therefore important to model their performance effectively. This paper describes a simulation model which predicts the cumulative distribution function of I/O request response time in a RAID 0 system consisting of homogeneous zoned disk drives. The model is constructed...

    Provided By Imperial College London

  • White Papers // Jan 2014

    Preconditioners for Inexact Interior Point Methods for Predictive Control

    In this paper the authors presents a new method for solving a linear discrete-time Finite Horizon Optimal Control Problem (FHOCP) with quadratic cost and linear constraints on the states and inputs. Such a FHOCP needs to be solved online, at each sampling instant, in predictive control. In order to solve...

    Provided By Imperial College London

  • White Papers // Oct 2013

    High-Level Synthesis of Dynamic Data Structures: A Case Study Using Vivado HLS

    High-level synthesis promises a significant shortening of the FPGA design cycle when compared with design entry using Register Transfer Level (RTL) languages. Recent evaluations report that C-to-RTL flows can produce results with a quality close to hand-crafted designs. Algorithms which use dynamic, pointer-based data structures, which are common in software,...

    Provided By Imperial College London

  • White Papers // Oct 2013

    Managing Emergencies Optimally Using a Random Neural Network-Based Algorithm

    Emergency rescues require that first responders provide support to evacuate injured and other civilians who are obstructed by the hazards. In this case, the emergency personnel can take actions strategically in order to rescue people maximally, efficiently and quickly. The paper studies the effectiveness of a Random Neural Network (RNN)-based...

    Provided By Imperial College London

  • White Papers // Oct 2013

    SOAP: Structural Optimization of Arithmetic Expressions for High-Level Synthesis

    In this paper the authors introduce SOAP, a new tool to automatically optimize the structure of arithmetic expressions for FPGA implementation as part of a high level synthesis flow, taking into account axiomatic rules derived from real arithmetic, such as distributivity, associativity and others. They explicitly target an optimized area/accuracy...

    Provided By Imperial College London

  • White Papers // Jul 2013

    Embedded Predictive Control on an FPGA using the Fast Gradient Method

    Model Predictive Control (MPC) in resource constrained embedded platforms requires faster, cheaper and more power-efficient solvers for convex programs than is currently offered by software-based solutions. In this paper the authors present the first Field Programmable Gate Array (FPGA) implementation of a fast gradient solver for linear-quadratic MPC problems with...

    Provided By Imperial College London

  • White Papers // Jun 2013

    SQOWL2: Transactional Type Inference for OWL 2 DL in an RDBMS

    SQOWL2 is a compiler which allows an RDBMS to support sound reasoning of SROIQ(D) description logics, by implementing ontologies expressed in the OWL 2 DL language as a combination of tables and triggers in the RDBMS. The reasoning process is divided into two phases of classification of the T-Box and...

    Provided By Imperial College London

  • White Papers // Jun 2013

    FPGA-Based K-Means Clustering Using Tree-Based Data Structures

    K-means clustering is a popular technique for partitioning a data set into subsets of similar features. Due to their simple control flow and inherent fine-grain parallelism, K-means algorithms are well suited for hardware implementations, such as on Field Programmable Gate Arrays (FPGAs), to accelerate the computationally intensive calculation. However, the...

    Provided By Imperial College London

  • White Papers // May 2013

    PEPERCORN: Inferring Performance Models from Location Tracking Data

    Stochastic performance models are widely used to analyze the performance of systems that process customers and resources. However, the construction of such models is traditionally manual and therefore expensive, intrusive and prone to human error. In this paper, the authors introduce PEPERCORN, a Petri Net Performance Model (PNPM) construction tool,...

    Provided By Imperial College London

  • White Papers // May 2013

    Mobile Network Anomaly Detection and Mitigation: The NEMESYS Approach

    Mobile malware and mobile network attacks are becoming a significant threat that accompanies the increasing popularity of smart phones and tablets. Thus in this paper, the authors present their research vision that aims to develop a network-based security solution combining analytical modeling, simulation and learning, together with billing and control-plane...

    Provided By Imperial College London

  • White Papers // Apr 2013

    Low-Complexity Scheduling Policies for Energy Harvesting Communication Networks

    A time-slotted multiple access wireless system with N transmitting nodes, each equipped with an Energy Harvesting (EH) device and a rechargeable battery of finite capacity, is studied. The energy arrival process at each node is modeled as an independent two-state Markov process, such that a node either harvests one unit...

    Provided By Imperial College London

  • White Papers // Apr 2013

    Energy-Aware MPC Co-Design for DC-DC Converters

    In this paper, the authors propose an integrated controller design methodology for the implementation of energy-aware explicit Model Predictive Control (MPC) algorithms, illustrating the method on a DC-DC converter model. The power consumption of control algorithms is becoming increasingly important for low-power embedded systems, especially where complex digital control techniques,...

    Provided By Imperial College London

  • White Papers // Apr 2013

    Bayesian Service Demand Estimation with Gibbs Sampling

    Performance modeling of web applications involves the task of estimating service demands of requests at physical resources, such as CPUs. In this paper, the authors propose a service demand estimation algorithm based on a Markov Chain Monte Carlo (MCMC) technique, Gibbs sampling. Their methodology is widely applicable as it requires...

    Provided By Imperial College London

  • White Papers // Apr 2013

    An Offline Demand Estimation Method for Multi-Threaded Applications

    Parameterizing performance models for multithreaded enterprise applications requires finding the service rates offered by worker threads to the incoming requests. Statistical inference on monitoring data is here helpful to reduce the overheads of application profiling and to infer missing information. While linear regression of utilization data is often used to...

    Provided By Imperial College London

  • White Papers // Apr 2013

    A Predictive Control Solver for Low-Precision Data Representation

    The authors propose a method to efficiently exploit the nonstandard number representation of some embedded computer architectures for the solution of constrained LQR problems. The resulting quadratic programming problem is formulated to include auxiliary decision variables as well as the inputs and states. The new formulation introduces smaller round-off errors...

    Provided By Imperial College London

  • White Papers // Apr 2013

    Fitting Second-Order Acyclic Marked Markovian Arrival Processes

    Markovian Arrival Processes (MAPs) are a tractable class of point-processes useful to model correlated time series, such as those commonly found in network traces and system logs used in performance analysis and reliability evaluation. Marked MAPs (MMAPs) generalize MAPs by further allowing the modeling of multi-class traces, possibly with cross-correlation...

    Provided By Imperial College London

  • White Papers // Mar 2013

    Application Composition and Communication Optimization in Iterative Solvers Using FPGAs

    The authors consider the problem of minimizing communication with off-chip memory and composition of multiple linear algebra kernels in iterative solvers for solving large-scale eigen-value problems and linear systems of equations. While GPUs may offer higher throughput for individual kernels, overall application performance is limited by the inability to support...

    Provided By Imperial College London

  • White Papers // Mar 2013

    Accuracy-Performance Tradeoffs on an FPGA Through Overclocking

    Embedded applications can often demand stringent latency requirements. While high degrees of parallelism within custom FPGA-based accelerators may help to some extent, it may also be necessary to limit the precision used in the datapath to boost the operating frequency of the implementation. However, by reducing the precision, the engineer...

    Provided By Imperial College London

  • White Papers // Mar 2013

    Modelling Exogenous Variability in Cloud Deployments

    Describing exogenous variability in the resources used by a cloud application leads to stochastic performance models that are difficult to solve. In this paper, the authors describe the blending algorithm, a novel approximation for queuing network models immersed in a random environment. Random environments are Markov chain-based descriptions of time-varying...

    Provided By Imperial College London

  • White Papers // Nov 2012

    OFBench: an Enterprise Application Benchmark for Cloud Resource Management Studies

    The authors introduce OFBench, a new research benchmark for enterprise applications. OFBench is a load generator for the demo e-commerce component of the Apache OFBiz Enterprise Resource Planning (ERP) framework. ERP applications are increasingly important in the cloud market due to the growing popularity of Software-as-a-Service (SaaS) solutions; hence OFBench...

    Provided By Imperial College London

  • White Papers // Oct 2012

    WikiSensing: An Online Collaborative Approach for Sensor Data Management

    This paper presents a new methodology for collaborative sensor data management known as WikiSensing. It is a novel approach that incorporates online collaboration with sensor data management. The authors introduce the work on this research by describing the motivation and challenges of designing and developing an online collaborative sensor data...

    Provided By Imperial College London

  • White Papers // Jun 2012

    Lightweight Resource Scaling for Cloud Applications

    Elastic resource provisioning is a key feature of cloud computing, allowing users to scale up or down resource allocation for their applications at run-time. To date, most practical approaches to managing elasticity are based on allocation/de-allocation of the Virtual Machine (VM) instances to the application. This VM-level elasticity typically incurs...

    Provided By Imperial College London

  • White Papers // Jun 2012

    Resilient Emergency Evacuation Using Opportunistic Communications

    The authors describe an emergency Evacuation Support System (ESS) that employs short-range wireless communications among mobile devices carried by civilians. Emergency information is disseminated via opportunistic contacts between Communication Nodes (CNs), and each CN provides adaptive step-by-step navigation directions for its user during evacuation. Using mobile devices and opportunistic communications...

    Provided By Imperial College London

  • White Papers // Jun 2012

    FASTER: Facilitating Analysis and Synthesis Technologies for Effective Reconfiguration

    The FASTER project aims to ease the definition, implementation and use of dynamically changing hardware systems. The authors' motivation stems from the promise reconfigurable systems hold for achieving better performance and extending product functionality and lifetime via the addition of new features that work at hardware speed. This is a...

    Provided By Imperial College London

  • White Papers // Jun 2012

    Modelling Reconfigurable Systems in Event Driven Simulation

    Reconfigurable platforms allow hardware developers to customize their designs for specific applications. However, their adoption involves challenges in understanding and estimating the impact of various design parameters and approaches. This paper proposes a unified framework to model behavior of reconfigurable systems using an event driven simulation approach. This provides an...

    Provided By Imperial College London

  • White Papers // May 2012

    Privacy-Preserving Location and Mobility Management to Support Tether-Free Patients in Ad-Hoc Networks

    A major driver of healthcare cost is the inefficiencies associated keeping less-critical patients overnight in the hospital when these patients could be treated as outpatients and received comparable quality of care. To this end, the authors propose the concept of tether-free patient to support patient mobility and ensure privacy-preserving healthcare....

    Provided By Imperial College London

  • White Papers // May 2012

    Reconfigurable Design Automation by High-Level Exploration

    In this paper the authors describe a novel approach for design automation of general-purpose reconfigurable computing applications, which combines design space exploration with transformation-based high-level feedback of performance results obtained from a detailed implementation. This approach enhances effectiveness of high-level exploration by using performance estimates to guide the selection of...

    Provided By Imperial College London

  • White Papers // May 2012

    A Reconfigurable Computing Approach for Efficient and Scalable Parallel Graph Exploration

    In many application domains, data are represented using large graphs involving millions of vertices and billions of edges. Graph exploration algorithms, such as Breadth-First Search (BFS), are largely dominated by memory latency and are challenging to process efficiently. In this paper, the authors present a reconfigurable hardware methodology for efficient...

    Provided By Imperial College London

  • White Papers // Mar 2012

    MODACLOUDS: A Model-Driven Approach for the Design and Execution of Applications on Multiple Clouds

    Cloud computing is emerging as a major trend in the ICT industry. While most of the attention of the research community is focused on considering the perspective of the cloud providers, offering mechanisms to support scaling of resources and interoperability and federation between clouds, the perspective of developers and operators...

    Provided By Imperial College London

  • White Papers // Mar 2012

    MODACLOUDS, a Model-Driven Approach for the Design and Execution of Applications on Multiple Clouds

    Cloud computing is emerging as a major trend in the ICT industry. While most of the attention of the research community is focused on considering the perspective of the Cloud providers, offering mechanisms to support scaling of resources and interoperability and federation between Clouds, the perspective of developers and operators...

    Provided By Imperial College London

  • White Papers // Mar 2012

    NaaS: Network-as-a-Service in the Cloud

    Cloud computing realises the vision of utility computing. Tenants can benefit from on-demand provisioning of computational resources according to a pay-per-use model and can outsource hardware purchases and maintenance. Tenants, however, have only limited visibility and control over network resources. Even for simple tasks, tenants must resort to inefficient overlay...

    Provided By Imperial College London

  • White Papers // Mar 2012

    Pervasive Emergency Support Systems for Building Evacuation

    An emergency situation taking place inside a confined space, such as a building, is a challenging task due to the presence of dynamic conditions. Pervasive systems can prove beneficial for the evacuation procedure, as they can provide directions to the evacuees regarding the best available exit. In this paper, the...

    Provided By Imperial College London

  • White Papers // Mar 2012

    WIQ:Work-Intensive Query Scheduling for In-Memory Database Systems

    The authors propose a novel admission control policy for database queries. Their methodology uses system measurements of CPU utilization and query backlogs to determine interference between queries in execution on the same database server. Query interference may arise due to the concurrent access of hardware and software resources and can...

    Provided By Imperial College London

  • White Papers // Jan 2012

    Towards a Program Logic for JavaScript

    JavaScript has become the most widely used language for client-side web programming. The dynamic nature of JavaScript makes understanding its code notoriously difficult, leading to buggy programs and a lack of adequate static-analysis tools. The authors believe that logical reasoning has much to offer JavaScript: a simple description of program...

    Provided By Imperial College London

  • White Papers // Dec 2011

    FPGA Paranoia: Testing Numerical Properties of FPGA Floating Point IP-Cores

    In the early days of computing, hardware platforms were developed independently and created their own conventions for floating point to suit their underlying hardware architecture, but this meant computer programmers had to understand these conventions when designing their algorithms, and adapt their algorithms when porting to new platforms. As a...

    Provided By Imperial College London

  • White Papers // Dec 2011

    Migrating Auctioneers on Internet Auctions for Improved Utility and Performance

    The paper studies a technique to improve the utility and performance of an automated auction application where the auctioneer and bidders communicate through the Internet. The lack of quality-of-service guarantees from site to site can severely influence the results of an auction by affecting the seller's income rate, auction fairness,...

    Provided By Imperial College London

  • White Papers // Jul 2010

    Shared and Searchable Encrypted Data for Untrusted Servers

    Current security mechanisms are not suitable for organisations that outsource their data management to untrusted servers. Encrypting and decrypting sensitive data at the client side is the normal approach in this situation but has high communication and computation overheads if only a subset of the data is required, for example,...

    Provided By Imperial College London

  • White Papers // Sep 2009

    Automatic Optimisation of MapReduce Designs by Geometric Programming

    Many important applications can be expressed using the MapReduce pattern, where a computation is decomposed into a map phase on which each element of source data is independently operated, followed by a reduce phase in which the mapped elements are combined with an associative operator. The authors develop an approach...

    Provided By Imperial College London

  • White Papers // Sep 2009

    Methodology for Designing Statically Scheduled Application-Specific SDRAM Controllers using Constrained Local Search

    In this paper the authors present an automatic method for generating valid SDRAM command schedules which obey the timing restrictions of DDR2 memory from a set of memory references. These generated schedules can be implemented using a static memory controller. A complete knowledge of the sequence of memory references in...

    Provided By Imperial College London

  • White Papers // Sep 2009

    Performance Comparison of GPU and FPGA architectures for the SVM Training Problem

    The Support Vector Machine (SVM) is a popular supervised learning method, providing high accuracy in many classification and regression tasks. However, its training phase is a computationally expensive task. In this paper, the authors focus on the acceleration of this phase and a geometric approach to SVM training based on...

    Provided By Imperial College London

  • White Papers // Jun 2009

    Area Estimation and Optimisation of FPGA Routing Fabrics

    In this paper the authors present a methodology for estimating and optimizing FPGA routing fabrics using high-level modeling and convex optimization techniques. Experimental methods for exploring design spaces suffer from expensive computation time, which is exacerbated by increased dimensionality due to the larger number of architectural parameters. In this paper...

    Provided By Imperial College London

  • White Papers // Oct 2008

    Parallel Architectures for Model Predictive Control

    In this paper the authors survey recent developments in parallel computer architecture, focusing on the field programmable gate array and the graphics processor. They aim to illustrate the potential of these architectures for the type of high-speed numerical computation required in online optimization for model predictive control. While significant performance...

    Provided By Imperial College London

  • White Papers // Mar 2009

    More Flops or More Precision? Accuracy Parameterizable Linear Equation Solvers for Model Predictive Control

    In this paper the authors exploit FPGA flexibility in the context of accelerating the solution of many small systems of linear equations, a problem central to Model Predictive Control (MPC). The main observation exploited by this work is the distinction between accuracy (meaning the degree of correctness of a final...

    Provided By Imperial College London

  • White Papers // Jun 2009

    Data Reuse Exploration under an On-Chip Memory Constraint for Low Power FPGA-Based Systems

    Contemporary FPGA-based reconfigurable systems have been widely used to implement data dominated applications. In these applications data transfer and storage consume a large proportion of the system energy. Exploiting data reuse can introduce significant power savings, but also introduces the extra requirement for on-chip memory. To aid data reuse design...

    Provided By Imperial College London

  • White Papers // Nov 2008

    A High Throughput FPGA-Based Floating Point Conjugate Gradient Implementation for Dense Matrices

    Recent developments in the capacity of modern Field Programmable Gate Arrays (FPGAs) have significantly expanded their applications. One such field is the acceleration of scientific computation and one type of calculation that is common-place in scientific computation is the solution of systems of linear equations. A method that has proven...

    Provided By Imperial College London

  • White Papers // Dec 2008

    Word-Length Optimization and Error Analysis of a Multivariate Gaussian Random Number Generator

    Monte carlo simulation is one of the most widely used techniques for computationally intensive simulations in mathematical analysis and modeling. A multivariate gaussian random number generator is one of the main building blocks of such a system. Field Programmable Gate Arrays (FPGAs) are gaining increased popularity as an alternative means...

    Provided By Imperial College London

  • White Papers // Oct 2008

    Co-optimisation of Datapath and Memory in Outer Loop Pipelining

    When targeting algorithms to FPGAs both the array to memory assignment and the selection of data reuse structures should be considered to maximize performance. In this paper the authors present an Integer Linear Programming formulation for the combined problem of array to memory assignment and data reuse selection. They include...

    Provided By Imperial College London

  • White Papers // May 2012

    Reconfigurable Design Automation by High-Level Exploration

    In this paper the authors describe a novel approach for design automation of general-purpose reconfigurable computing applications, which combines design space exploration with transformation-based high-level feedback of performance results obtained from a detailed implementation. This approach enhances effectiveness of high-level exploration by using performance estimates to guide the selection of...

    Provided By Imperial College London

  • White Papers // Jun 2011

    CusComNet: A Customisable Network for Reconfigurable Heterogeneous Clusters

    Computer clusters equipped with reconfigurable accelerators have shown promise in high performance computing. This paper explores novel ways of customizing data communication between accelerator nodes, which is often a bottleneck when scaling up the cluster size. Based on the direct connection of high speed serial links between advanced reconfigurable devices,...

    Provided By Imperial College London

  • White Papers // Jun 2011

    Unifying Finite Difference Option-pricing for Hardware Acceleration

    Explicit finite difference method is widely used in finance for pricing many kinds of options. Its regular computational pattern makes it an ideal candidate for acceleration using reconfigurable hardware. However, because the corresponding hardware designs must be optimized both for the specific option and for the target platform, it is...

    Provided By Imperial College London

  • White Papers // Oct 2013

    SOAP: Structural Optimization of Arithmetic Expressions for High-Level Synthesis

    In this paper the authors introduce SOAP, a new tool to automatically optimize the structure of arithmetic expressions for FPGA implementation as part of a high level synthesis flow, taking into account axiomatic rules derived from real arithmetic, such as distributivity, associativity and others. They explicitly target an optimized area/accuracy...

    Provided By Imperial College London

  • White Papers // Oct 2013

    High-Level Synthesis of Dynamic Data Structures: A Case Study Using Vivado HLS

    High-level synthesis promises a significant shortening of the FPGA design cycle when compared with design entry using Register Transfer Level (RTL) languages. Recent evaluations report that C-to-RTL flows can produce results with a quality close to hand-crafted designs. Algorithms which use dynamic, pointer-based data structures, which are common in software,...

    Provided By Imperial College London

  • White Papers // Jul 2013

    Embedded Predictive Control on an FPGA using the Fast Gradient Method

    Model Predictive Control (MPC) in resource constrained embedded platforms requires faster, cheaper and more power-efficient solvers for convex programs than is currently offered by software-based solutions. In this paper the authors present the first Field Programmable Gate Array (FPGA) implementation of a fast gradient solver for linear-quadratic MPC problems with...

    Provided By Imperial College London

  • White Papers // Jun 2013

    FPGA-Based K-Means Clustering Using Tree-Based Data Structures

    K-means clustering is a popular technique for partitioning a data set into subsets of similar features. Due to their simple control flow and inherent fine-grain parallelism, K-means algorithms are well suited for hardware implementations, such as on Field Programmable Gate Arrays (FPGAs), to accelerate the computationally intensive calculation. However, the...

    Provided By Imperial College London

  • White Papers // Mar 2013

    Application Composition and Communication Optimization in Iterative Solvers Using FPGAs

    The authors consider the problem of minimizing communication with off-chip memory and composition of multiple linear algebra kernels in iterative solvers for solving large-scale eigen-value problems and linear systems of equations. While GPUs may offer higher throughput for individual kernels, overall application performance is limited by the inability to support...

    Provided By Imperial College London

  • White Papers // Mar 2013

    Accuracy-Performance Tradeoffs on an FPGA Through Overclocking

    Embedded applications can often demand stringent latency requirements. While high degrees of parallelism within custom FPGA-based accelerators may help to some extent, it may also be necessary to limit the precision used in the datapath to boost the operating frequency of the implementation. However, by reducing the precision, the engineer...

    Provided By Imperial College London

  • White Papers // Apr 2013

    Energy-Aware MPC Co-Design for DC-DC Converters

    In this paper, the authors propose an integrated controller design methodology for the implementation of energy-aware explicit Model Predictive Control (MPC) algorithms, illustrating the method on a DC-DC converter model. The power consumption of control algorithms is becoming increasingly important for low-power embedded systems, especially where complex digital control techniques,...

    Provided By Imperial College London

  • White Papers // Apr 2013

    A Predictive Control Solver for Low-Precision Data Representation

    The authors propose a method to efficiently exploit the nonstandard number representation of some embedded computer architectures for the solution of constrained LQR problems. The resulting quadratic programming problem is formulated to include auxiliary decision variables as well as the inputs and states. The new formulation introduces smaller round-off errors...

    Provided By Imperial College London

  • White Papers // Dec 2011

    FPGA Paranoia: Testing Numerical Properties of FPGA Floating Point IP-Cores

    In the early days of computing, hardware platforms were developed independently and created their own conventions for floating point to suit their underlying hardware architecture, but this meant computer programmers had to understand these conventions when designing their algorithms, and adapt their algorithms when porting to new platforms. As a...

    Provided By Imperial College London

  • White Papers // Oct 2011

    Correctly Rounded Constant Integer Division via Multiply-Add

    Implementing integer division in hardware is expensive when compared to multiplication. In the case where the divisor is a constant, expensive integer division algorithms can be replaced by cheaper integer multiplications and additions. This paper presents the conditions for multiply-add schemes to perform correctly rounded unsigned invariant integer division under...

    Provided By Imperial College London

  • White Papers // Jun 2010

    Mapping Multiple Multivariate Gaussian Random Number Generators on an FPGA

    A Multi-Variate Gaussian Random Number Generator (MVGRNG) is an essential block for many hardware designs, including monte carlo simulations. These simulations are usually used in applications such as statistical physics and financial mathematics. Field Programmable Gate Arrays (FPGAs) are often used to implement these generators as the design can be...

    Provided By Imperial College London

  • White Papers // Mar 2010

    Automated Precision Analysis: A Polynomial Algebraic Approach

    When migrating an algorithm onto hardware, the potential saving that can be obtained by tuning the precision used in the algorithm to meet a range or error specification is often overlooked; the major reason is that it is hard to choose a number system which can guarantee any such specification...

    Provided By Imperial College London

  • White Papers // Mar 2010

    A Scripting Engine for Combining Design Transformations

    To implement complex designs quickly, designers increasingly turn to high-level design descriptions, which ease design capture and design space exploration, and allow rapid prototyping and fast time to market. This paper describes a scripting engine based on the python language and the ROSE compiler framework. The authors' scripting engine supports...

    Provided By Imperial College London

  • White Papers // Dec 2009

    Design of a Financial Application Driven Multivariate Gaussian Random Number Generator for an FPGA

    A Multi-Variate Gaussian Random Number Generator (MVGRNG) is a pre-requisite for most monte carlo simulations for financial applications, especially those that involve many correlated assets. In recent years, Field Programmable Gate Arrays (FPGAs) have received a lot of attention as a target platform for the implementation of such a generator...

    Provided By Imperial College London

  • White Papers // Jan 2014

    Preconditioners for Inexact Interior Point Methods for Predictive Control

    In this paper the authors presents a new method for solving a linear discrete-time Finite Horizon Optimal Control Problem (FHOCP) with quadratic cost and linear constraints on the states and inputs. Such a FHOCP needs to be solved online, at each sampling instant, in predictive control. In order to solve...

    Provided By Imperial College London

  • White Papers // Dec 2009

    A Fused Hybrid Floating-Point and Fixed-Point Dot-product for FPGAs

    Dot-products are one of the essential and recurrent building blocks in scientific computing, and often take-up a large proportion of the scientific acceleration circuitry. The acceleration of dot-products is very well suited for Field Programmable Gate Arrays (FPGAs) since these devices can be configured to employ wide parallelism, deep pipelining...

    Provided By Imperial College London

  • White Papers // Dec 2009

    Optimising Memory Bandwidth Use for Matrix-Vector Multiplication in Iterative Methods

    Computing the solution to a system of linear equations is a fundamental problem in scientific computing, and its acceleration has drawn wide interest in the FPGA community. One class of algorithms to solve these systems, iterative methods, has drawn particular interest, with recent literature showing large performance improvements over General...

    Provided By Imperial College London

  • White Papers // Aug 2009

    Concurrently Optimizing FPGA Architecture Parameters and Transistor Sizing: Implications for FPGA Design

    This paper presents a method that combines high-level and low-level architecture parameter exploration. The paper builds on an increasing body of work concerned with modeling reconfigurable architectures, and presents a full area and delay model of an FPGA. The optimization of this model is based on the use of Geometric...

    Provided By Imperial College London

  • White Papers // Sep 2011

    Parallel Move Blocking Model Predictive Control

    In this paper the authors propose the use of parallel computing architectures (multi-core, FPGA and GPU) to implement a parallel move blocking Model Predictive Control (MPC) algorithm where multiple, but smaller optimization problems are solved simultaneously. Since these problems are solved in parallel, the computational delay is reduced when compared...

    Provided By Imperial College London

  • White Papers // Jan 2011

    Application Specific Memory Access, Reuse and Reordering for SDRAM

    The efficient use of bandwidth available on an external SDRAM interface is strongly dependent on the sequence of addresses requested. The On-chip memory buffers can make possible data reuse and request reordering which together ensure bandwidth on an SDRAM interface is used efficiently. This paper outlines an automated procedure for...

    Provided By Imperial College London

  • White Papers // Sep 2010

    An FPGA Implementation of a Sparse Quadratic Programming Solver for Constrained Predictive Control

    Model Predictive Control (MPC) is an advanced industrial control technique that relies on the solution of a Quadratic Programming (QP) problem at every sampling instant to determine the input action required to control the current and future behavior of a physical system. Its ability in handling large Multiple Input Multiple...

    Provided By Imperial College London

  • White Papers // Aug 2011

    Solving a Positive Definite System of Linear Equations Via the Matrix Exponential

    The authors present a new direct algorithm for solving a system of linear equations with a positive definite matrix by discretizing a continuous-time dynamical system for a large sampling time. The obtained algorithm is highly fine-grain parallelizable and its computational complexity grows logarithmically with respect to the condition number of...

    Provided By Imperial College London

  • White Papers // Sep 2010

    FPGA Implementation of an Interior Point Solver for Linear Model Predictive Control

    Automatic control, the process of measuring, computing, and applying an input to control the behavior of a physical system, is ubiquitous in engineering and industry. Model Predictive Control (MPC) is an advanced control technology that has been very successful in the chemical process industries due to its ability to handle...

    Provided By Imperial College London

  • White Papers // Sep 2010

    A Fast Well-conditioned Interior Point Method for Predictive Control

    Interior Point Methods (IPMs) have proven to be an efficient way of solving quadratic programming problems in predictive control. A linear system of equations needs to be solved in each iteration of an IPM. The ill-conditioning of this linear system in the later iterations of the IPM prevents the use...

    Provided By Imperial College London

  • White Papers // May 2012

    A Reconfigurable Computing Approach for Efficient and Scalable Parallel Graph Exploration

    In many application domains, data are represented using large graphs involving millions of vertices and billions of edges. Graph exploration algorithms, such as Breadth-First Search (BFS), are largely dominated by memory latency and are challenging to process efficiently. In this paper, the authors present a reconfigurable hardware methodology for efficient...

    Provided By Imperial College London

  • White Papers // Jun 2012

    Modelling Reconfigurable Systems in Event Driven Simulation

    Reconfigurable platforms allow hardware developers to customize their designs for specific applications. However, their adoption involves challenges in understanding and estimating the impact of various design parameters and approaches. This paper proposes a unified framework to model behavior of reconfigurable systems using an event driven simulation approach. This provides an...

    Provided By Imperial College London