Design of Intellectual Property-Based Hardware Blocks Integrable with Embedded RISC Processors

The main focus of this thesis is to research methods, architecture, and implementation of hardware acceleration for a Reduced Instruction Set Computer (RISC) platform. The target platform is a single-core general-purpose embedded processor (the COFFEE core) which was developed by our group at Tampere University of Technology. The COFFEE core alone cannot meet the requirements of the modern applications due to the lack of several components of which the Memory Management Unit (MMU) is one of the prominent ones. Since the MMU is one of the main requirements of today’s processors, COFFEE with no MMU was not able to run an operating system. In the design of the MMU, we employed two additional micro-Translation-Lookaside Buffers (TLBs) to speed up the translation process, as well as minimizing congestions of the data/instruction address translations with a unified TLB. The MMU is tightly-coupled with the COFFEE RISC core through the Peripheral Control Block (PCB) interface of the core. The hardware implementation, alongside some optimization techniques and post synthesis results are presented, as well.Another intention of this work is to prepare a reconfigurable platform to send and receive data packets of the next generation wireless communications. Hence, we will further discuss a recently emerged wireless modulation technique known as Non-Contiguous Orthogonal Frequency Division Multiplexing (NC-OFDM), a promising technique to alleviate spectrum scarcity problem. However, one of the primary concerns in such systems is the synchronization. To that end, we developed a reconfigurable hardware component to perform as a synchronizer. The developed module exploits Partial Reconfiguration (PR) feature in order to reconfigure itself. Eventually, we will come up with several architectural choices for systems with different limiting factors such as power consumption, operating frequency, and silicon area. The synchronizer can be loosely-coupled via one of the available co-processor slots of the target processor, the COFFEE RISC core.In addition, we are willing to improve the versatility of the COFFEE core even in industrial use cases. Hence, we developed a reconfigurable hardware component capable of operating in the Controller Area Network (CAN) protocol. In the first step of this implementation, we mainly concentrate on receiving, decoding, and extracting the data segment of a CAN-based packet. Moreover, this hardware block can reconfigure itself on-the-fly to operate on different data frames. More details regarding hardware implementation issues, as well as post synthesis results are also presented. The CAN module is loosely-coupled with the COFFEE RISC processor through one of the available co-processor block

Recent Results on the Implementation of a Burst Error and Burst Erasure Channel Emulator Using an FPGA Architecture

The behaviour of a transmission channel may be simulated using the performance abilities of current generation multiprocessing hardware, namely, a multicore Central Processing Unit (CPU), a general purpose Graphics Processing Unit (GPU), or a Field Programmable Gate Array (FPGA). These were investigated by Cullinan et al. in a recent paper (published in 2012) where these three devices capabilities were compared to determine which device would be best suited towards which specific task. In particular, it was shown that, for the application which is objective of our work (i.e., for a transmission channel simulation), the FPGA is 26.67 times faster than the GPU and 10.76 times faster than the CPU. Motivated by these results, in this paper we propose and present a direct hardware emulation. In particular, a Cyclone II FPGA architecture is implemented to simulate a burst error channel behaviour, in which errors are clustered together, and a burst erasure channel behaviour, in which the erasures are clustered together. The results presented in the paper are valid for any FPGA architecture that may be considered for this scope

On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds

Fifth generation (5G) mobile communication systems have entered the stage of commercial development, providing users with new services and improved user experiences as well as offering a host of novel opportunities to various industries. However, 5G still faces many challenges. To address these challenges, international industrial, academic, and standards organizations have commenced research on sixth generation (6G) wireless communication systems. A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc. Although ITU-R has been working on the 6G vision and it is expected to reach a consensus on what 6G will be by mid-2023, the related global discussions are still wide open and the existing literature has identified numerous open issues. This paper first provides a comprehensive portrayal of the 6G vision, technical requirements, and application scenarios, covering the current common understanding of 6G. Then, a critical appraisal of the 6G network architecture and key technologies is presented. Furthermore, existing testbeds and advanced 6G verification platforms are detailed for the first time. In addition, future research directions and open challenges are identified for stimulating the on-going global debate. Finally, lessons learned to date concerning 6G networks are discussed

Energy-Efficient Computing for Mobile Signal Processing

Mobile devices have rapidly proliferated, and deployment of handheld devices continues to increase at a spectacular rate. As today's devices not only support advanced signal processing of wireless communication data but also provide rich sets of applications, contemporary mobile computing requires both demanding computation and efficiency. Most mobile processors combine general-purpose processors, digital signal processors, and hardwired application-specific integrated circuits to satisfy their high-performance and low-power requirements. However, such a heterogeneous platform is inefficient in area, power and programmability. Improving the efficiency of programmable mobile systems is a critical challenge and an active area of computer systems research. SIMD (single instruction multiple data) architectures are very effective for data-level-parallelism intense algorithms in mobile signal processing. However, new characteristics of advanced wireless/multimedia algorithms require architectural re-evaluation to achieve better energy efficiency. Therefore, fourth generation wireless protocol and high definition mobile video algorithms are analyzed to enhance a wide-SIMD architecture. The key enhancements include 1) programmable crossbar to support complex data alignment, 2) SIMD partitioning to support fine-grain SIMD computation, and 3) fused operation to support accelerating frequently used instruction pairs. Near-threshold computation has been attractive in low-power architecture research because it balances performance and power. To further improve energy efficiency in mobile computing, near-threshold computation is applied to a wide SIMD architecture. This proposed near-threshold wide SIMD architecture-Diet SODA-presents interesting architectural design decisions such as 1) very wide SIMD datapath to compensate for degraded performance induced by near-threshold computation and 2) scatter-gather data prefetcher to exploit large latency gap between memory and the SIMD datapath. Although near-threshold computation provides excellent energy efficiency, it suffers from increased delay variations. A systematic study of delay variations in near-threshold computing is performed and simple techniques-structural duplication and voltage/frequency margining-are explored to tolerate and mitigate the delay variations in near-threshold wide SIMD architectures. This dissertation analyzes representative wireless/multimedia mobile signal processing algorithms, proposes an energy-efficient programmable platform, and evaluates performance and power. A main theme of this dissertation is that the performance and efficiency of programmable embedded systems can be significantly improved with a combination of parallel SIMD and near-threshold computations.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/86356/1/swseo_1.pd

Algorithm Optimization and Hardware Acceleration for Machine Learning Applications on Low-energy Systems

Machine learning (ML) has been extensively employed for strategy optimization, decision making, data classification, etc. While ML shows great triumph in its application field, the increasing complexity of the learning models introduces neoteric challenges to the ML system designs. On the one hand, the applications of ML on resource-restricted terminals, like mobile computing and IoT devices, are prevented by the high computational complexity and memory requirement. On the other hand, the massive parameter quantity for the modern ML models appends extra demands on the system\u27s I/O speed and memory size. This dissertation investigates feasible solutions for those challenges with software-hardware co-design