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

A CAD Tool for Synthesizing Optimized Variants of Altera\u27s Nios II Soft-Core Processor

Soft-core processors offer embedded system designers the benefits of customization, flexibility and reusability. Altera\u27s NIOS II soft-core processor is a popular, commercially available soft-core processor that can be implemented on a variety of Altera FPGAs. In this thesis, the Nios II soft-core processor from Altera Corporation was studied and a VHDL implementation, called UW_Nios II, was developed. UW_Nios II was developed to enable us to perform design space exploration (DSE) for the Nios II processor. It was evaluated and compared with Altera Nios II and shown to be competitive. SCBuild is an existing CAD tool that was developed to enable DSE of soft-core processors. We modified SCBuild to automatically explore the design space of the UW_Nios II using a genetic algorithm. This tool can accurately estimate the area and critical path delay of different variants of the UW_Nios II on a field programmable gate array. Through experiments conducted using SCBuild, it was shown that employing a genetic algorithm to explore the design space of parameterized Nios II core, with a large design space, helps designers find optimized variants of UW_Nios II

BRISC-V: An Open-Source Architecture Design Space Exploration Toolbox

In this work, we introduce a platform for register-transfer level (RTL) architecture design space exploration. The platform is an open-source, parameterized, synthesizable set of RTL modules for designing RISC-V based single and multi-core architecture systems. The platform is designed with a high degree of modularity. It provides highly-parameterized, composable RTL modules for fast and accurate exploration of different RISC-V based core complexities, multi-level caching and memory organizations, system topologies, router architectures, and routing schemes. The platform can be used for both RTL simulation and FPGA based emulation. The hardware modules are implemented in synthesizable Verilog using no vendor-specific blocks. The platform includes a RISC-V compiler toolchain to assist in developing software for the cores, a web-based system configuration graphical user interface (GUI) and a web-based RISC-V assembly simulator. The platform supports a myriad of RISC-V architectures, ranging from a simple single cycle processor to a multi-core SoC with a complex memory hierarchy and a network-on-chip. The modules are designed to support incremental additions and modifications. The interfaces between components are particularly designed to allow parts of the processor such as whole cache modules, cores or individual pipeline stages, to be modified or replaced without impacting the rest of the system. The platform allows researchers to quickly instantiate complete working RISC-V multi-core systems with synthesizable RTL and make targeted modifications to fit their needs. The complete platform (including Verilog source code) can be downloaded at https://ascslab.org/research/briscv/explorer/explorer.html.Comment: In Proceedings of the 2019 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA '19

FPGA-Based Real-Time Embedded System for RISS/GPS Integrated Navigation

Navigation algorithms integrating measurements from multi-sensor systems overcome the problems that arise from using GPS navigation systems in standalone mode. Algorithms which integrate the data from 2D low-cost reduced inertial sensor system (RISS), consisting of a gyroscope and an odometer or wheel encoders, along with a GPS receiver via a Kalman filter has proved to be worthy in providing a consistent and more reliable navigation solution compared to standalone GPS receivers. It has been also shown to be beneficial, especially in GPS-denied environments such as urban canyons and tunnels. The main objective of this paper is to narrow the idea-to-implementation gap that follows the algorithm development by realizing a low-cost real-time embedded navigation system capable of computing the data-fused positioning solution. The role of the developed system is to synchronize the measurements from the three sensors, relative to the pulse per second signal generated from the GPS, after which the navigation algorithm is applied to the synchronized measurements to compute the navigation solution in real-time. Employing a customizable soft-core processor on an FPGA in the kernel of the navigation system, provided the flexibility for communicating with the various sensors and the computation capability required by the Kalman filter integration algorithm

A template-based methodology for efficient microprocessor and FPGA accelerator co-design

Embedded applications usually require Software/Hardware (SW/HW) designs to meet the hard timing constraints and the required design flexibility. Exhaustive exploration for SW/HW designs is a very time consuming task, while the adhoc approaches and the use of partially automatic tools usually lead to less efficient designs. To support a more efficient codesign process for FPGA platforms we propose a systematic methodology to map an application to SW/HW platform with a custom HW accelerator and a microprocessor core. The methodology mapping steps are expressed through parametric templates for the SW/HW Communication Organization, the Foreground (FG) Memory Management and the Data Path (DP) Mapping. Several performance-area tradeoff design Pareto points are produced by instantiating the templates. A real-time bioimaging application is mapped on a FPGA to evaluate the gains of our approach, i.e. 44,8% on performance compared with pure SW designs and 58% on area compared with pure HW designs

The Potential for a GPU-Like Overlay Architecture for FPGAs

We propose a soft processor programming model and architecture inspired by graphics processing units (GPUs) that are well-matched to the strengths of FPGAs, namely, highly parallel and pipelinable computation. In particular, our soft processor architecture exploits multithreading, vector operations, and predication to supply a floating-point pipeline of 64 stages via hardware support for up to 256 concurrent thread contexts. The key new contributions of our architecture are mechanisms for managing threads and register files that maximize data-level and instruction-level parallelism while overcoming the challenges of port limitations of FPGA block memories as well as memory and pipeline latency. Through simulation of a system that (i) is programmable via NVIDIA's high-level Cg language, (ii) supports AMD's CTM r5xx GPU ISA, and (iii) is realizable on an XtremeData XD1000 FPGA-based accelerator system, we demonstrate the potential for such a system to achieve 100% utilization of a deeply pipelined floating-point datapath

Design and resource management of reconfigurable multiprocessors for data-parallel applications

FPGA (Field-Programmable Gate Array)-based custom reconfigurable computing machines have established themselves as low-cost and low-risk alternatives to ASIC (Application-Specific Integrated Circuit) implementations and general-purpose microprocessors in accelerating a wide range of computation-intensive applications. Most often they are Application Specific Programmable Circuiits (ASPCs), which are developer programmable instead of user programmable. The major disadvantages of ASPCs are minimal programmability, and significant time and energy overheads caused by required hardware reconfiguration when the problem size outnumbers the available reconfigurable resources; these problems are expected to become more serious with increases in the FPGA chip size. On the other hand, dominant high-performance computing systems, such as PC clusters and SMPs (Symmetric Multiprocessors), suffer from high communication latencies and/or scalability problems. This research introduces low-cost, user-programmable and reconfigurable MultiProcessor-on-a-Programmable-Chip (MPoPC) systems for high-performance, low-cost computing. It also proposes a relevant resource management framework that deals with performance, power consumption and energy issues. These semi-customized systems reduce significantly runtime device reconfiguration by employing userprogrammable processing elements that are reusable for different tasks in large, complex applications. For the sake of illustration, two different types of MPoPCs with hardware FPUs (floating-point units) are designed and implemented for credible performance evaluation and modeling: the coarse-grain MIMD (Multiple-Instruction, Multiple-Data) CG-MPoPC machine based on a processor IP (Intellectual Property) core and the mixed-mode (MIMD, SIMD or M-SIMD) variant-grain HERA (HEterogeneous Reconfigurable Architecture) machine. In addition to alleviating the above difficulties, MPoPCs can offer several performance and energy advantages to our data-parallel applications when compared to ASPCs; they are simpler and more scalable, and have less verification time and cost. Various common computation-intensive benchmark algorithms, such as matrix-matrix multiplication (MMM) and LU factorization, are studied and their parallel solutions are shown for the two MPoPCs. The performance is evaluated with large sparse real-world matrices primarily from power engineering. We expect even further performance gains on MPoPCs in the near future by employing ever improving FPGAs. The innovative nature of this work has the potential to guide research in this arising field of high-performance, low-cost reconfigurable computing. The largest advantage of reconfigurable logic lies in its large degree of hardware customization and reconfiguration which allows reusing the resources to match the computation and communication needs of applications. Therefore, a major effort in the presented design methodology for mixed-mode MPoPCs, like HERA, is devoted to effective resource management. A two-phase approach is applied. A mixed-mode weighted Task Flow Graph (w-TFG) is first constructed for any given application, where tasks are classified according to their most appropriate computing mode (e.g., SIMD or MIMD). At compile time, an architecture is customized and synthesized for the TFG using an Integer Linear Programming (ILP) formulation and a parameterized hardware component library. Various run-time scheduling schemes with different performanceenergy objectives are proposed. A system-level energy model for HERA, which is based on low-level implementation data and run-time statistics, is proposed to guide performance-energy trade-off decisions. A parallel power flow analysis technique based on Newton\u27s method is proposed and employed to verify the methodology

Further Specialization of Clustered VLIW Processors: A MAP Decoder for Software Defined Radio

Turbo codes are extensively used in current communications standards and have a promising outlook for future generations. The advantages of software defined radio, especially dynamic reconfiguration, make it very attractive in this multi-standard scenario. However, the complex and power consuming implementation of the maximum a posteriori (MAP) algorithm, employed by turbo decoders, sets hurdles to this goal. This work introduces an ASIP architecture for the MAP algorithm, based on a dual-clustered VLIW processor. It displays the good performance of application specific designs along with the versatility of processors, which makes it compliant with leading edge standards. The machine deals with multi-operand instructions in an innovative way, the fetching and assertion of data is serialized and the addressing is automatized and transparent for the programmer. The performance-area trade-off of the proposed architecture achieves a throughput of 8 cycles per symbol with very low power dissipation