Accelerated Financial Applications through Specialized Hardware, FPGA

This project will investigate Field Programmable Gate Array (FPGA) technology in financial applications. FPGA implementation in high performance computing is still in its infancy. Certain companies like XtremeData inc. advertized speed improvements of 50 to 1000 times for DNA sequencing using FPGAs, while using an FPGA as a coprocessor to handle specific tasks provides two to three times more processing power. FPGA technology increases performance by parallelizing calculations. This project will specifically address speed and accuracy improvements of both fundamental and transcendental functions when implemented using FPGA technology. The results of this project will lead to a series of recommendations for effective utilization of FPGA technology in financial applications

Automatic Application-Specific Customization of Softcore Processor Microarchitecture, Masters Thesis, May 2006

Applications for constrained embedded systems are subject to strict runtime and resource utilization bounds. With soft core processors, application developers can customize the processor for their application, constrained by available hardware resources but aimed at high application performance. The more reconfigurable the processor is, the more options the application developers will have for customization and hence increased potential for improving application performance. However, such customization entails developing in-depth familiarity with all the parameters, in order to configure them effectively. This is typically infeasible, given the tight time-to-market pressure on the developers. Alternatively, developers could explore all possible configurations, but being exponential, this is infeasible even given only tens of parameters. This thesis presents an approach based on an assumption of parameter independence, for automatic microarchitecture customization. This approach is linear with the number of parameter values and hence, feasible and scalable. For the dimensions that we customize, namely application runtime and hardware resources, we formulate their costs as a constrained binary integer nonlinear optimization program. Though the results are not guaranteed to be optimal, we find they are near-optimal in practice. Our technique itself is general and can be applied to other design-space exploration problems

Study of the effects of SEU-induced faults on a pipeline protected microprocessor

This paper presents a detailed analysis of the behavior of a novel fault-tolerant 32-bit embedded CPU as compared to a default (non-fault-tolerant) implementation of the same processor during a fault injection campaign of single and double faults. The fault-tolerant processor tested is characterized by per-cycle voting of microarchitectural and the flop-based architectural states, redundancy at the pipeline level, and a distributed voting scheme. Its fault-tolerant behavior is characterized for three different workloads from the automotive application domain. The study proposes statistical methods for both the single and dual fault injection campaigns and demonstrates the fault-tolerant capability of both processors in terms of fault latencies, the probability of fault manifestation, and the behavior of latent faults

RITSim: distributed systemC simulation

Parallel or distributed simulation is becoming more than a novel way to speedup design evaluation; it is becoming necessary for simulating modern processors in a reasonable timeframe. As architectural features become faster, smaller, and more complex, designers are interested in obtaining detailed and accurate performance and power estimations. Uniprocessor simulators may not be able to meet such demands. The RITSim project uses SystemC to model a processor microarchitecture and memory subsystem in great detail. SystemC is a C++ library built on a discrete-event simulation kernel. Many projects have successfully implemented parallel discrete-event simulation (PDES) frameworks to distribute simulation among several hosts. The field promises significant simulation speedup, possibly leading to faster turnaround time in design space exploration and commercial production. However, parallel implementation of such simulators is not an easy task. It requires modification of the simulation kernel for effective partitioning and synchronization. This thesis explores PDES techniques and presents a distributed version of the SystemC simulation environment. With minimal user interaction, SystemC models can executed on a cluster of workstations using a message-passing library such as the Message Passing Interface (MPI). The implementation is designed for transparency; distribution and synchronization happen with little intervention by the model author. Modification of SystemC is fashioned to promote maintainability with future releases. Furthermore, only freely available libraries are used for maximum flexibility and portability

FIMSIM: A fault injection infrastructure for microarchitectural simulators

Fault injection is a widely used approach for experiment-based dependability evaluation in which faults can be injected to the hardware, to the simulator or to the software. Simulation based fault injection is more appealing for researchers, since it can be utilized at the early design stage of the processor. As such, it enables a preliminary analysis of the correlation between the criticality of circuit level faults and their impact on applications. However, the lack of publicly available fault injectors for microarchitecture level simulators brings extra burden of designing and implementing fault injectors to the researchers who evaluate microarchitecture dependability. In this study, we present FIMSIM, to the best of our knowledge, the first publicly available fault injection simulator at the microarchitecture level. FIMSIM is a compact tool which is capable of injecting transient, permanent, intermittent and multi-bit faults. Therefore, FIMSIM provides the opportunity to comprehensively evaluate the vulnerability of different microarchitectural structures against different fault models.Postprint (published version

Simulation-based Fault Injection with QEMU for Speeding-up Dependability Analysis of Embedded Software

Simulation-based fault injection (SFI) represents a valuable solu- tion for early analysis of software dependability and fault tolerance properties before the physical prototype of the target platform is available. Some SFI approaches base the fault injection strategy on cycle-accurate models imple- mented by means of Hardware Description Languages (HDLs). However, cycle- accurate simulation has revealed to be too time-consuming when the objective is to emulate the effect of soft errors on complex microprocessors. To overcome this issue, SFI solutions based on virtual prototypes of the target platform has started to be proposed. However, current approaches still present some draw- backs, like, for example, they work only for specific CPU architectures, or they require code instrumentation, or they have a different target (i.e., design errors instead of dependability analysis). To address these disadvantages, this paper presents an efficient fault injection approach based on QEMU, one of the most efficient and popular instruction-accurate emulator for several microprocessor architectures. As main goal, the proposed approach represents a non intrusive technique for simulating hardware faults affecting CPU behaviours. Perma- nent and transient/intermittent hardware fault models have been abstracted without losing quality for software dependability analysis. The approach mini- mizes the impact of the fault injection procedure in the emulator performance by preserving the original dynamic binary translation mechanism of QEMU. Experimental results for both x86 and ARM processors proving the efficiency and effectiveness of the proposed approach are presented

A configurable vector processor for accelerating speech coding algorithms

The growing demand for voice-over-packer (VoIP) services and multimedia-rich applications has made increasingly important the efficient, real-time implementation of low-bit rates speech coders on embedded VLSI platforms. Such speech coders are designed to substantially reduce the bandwidth requirements thus enabling dense multichannel gateways in small form factor. This however comes at a high computational cost which mandates the use of very high performance embedded processors. This thesis investigates the potential acceleration of two major ITU-T speech coding algorithms, namely G.729A and G.723.1, through their efficient implementation on a configurable extensible vector embedded CPU architecture. New scalar and vector ISAs were introduced which resulted in up to 80% reduction in the dynamic instruction count of both workloads. These instructions were subsequently encapsulated into a parametric, hybrid SISD (scalar processor)–SIMD (vector) processor. This work presents the research and implementation of the vector datapath of this vector coprocessor which is tightly-coupled to a Sparc-V8 compliant CPU, the optimization and simulation methodologies employed and the use of Electronic System Level (ESL) techniques to rapidly design SIMD datapaths

Coarse-grained reconfigurable array architectures

Coarse-Grained Reconfigurable Array (CGRA) architectures accelerate the same inner loops that benefit from the high ILP support in VLIW architectures. By executing non-loop code on other cores, however, CGRAs can focus on such loops to execute them more efficiently. This chapter discusses the basic principles of CGRAs, and the wide range of design options available to a CGRA designer, covering a large number of existing CGRA designs. The impact of different options on flexibility, performance, and power-efficiency is discussed, as well as the need for compiler support. The ADRES CGRA design template is studied in more detail as a use case to illustrate the need for design space exploration, for compiler support and for the manual fine-tuning of source code