Computation intensive kernels, such as convolutions, matrix multiplication and Fourier transform, are fundamental to edge-computing AI, signal processing and cryptographic applications. Interleaved-Multi-Threading (IMT) processor cores are interesting to pursue energy efficiency and low hardware cost for edge-computing, yet they need hardware acceleration schemes to run heavy computational workloads. Following a vector approach to accelerate computations, this study explores possible alternatives to implement vector coprocessing units in RISC-V cores, showing the synergy between IMT and data-level parallelism in the target workloads.

Functional safety is a key requirement in several application domains in which microprocessors are an essential part. A number of redundancy techniques have been developed with the common purpose of protecting circuits against single event upset (SEU) faults. In microprocessors, functional redundancy may be achieved through multi-core or simultaneous-multi-threading architectures, with techniques that are broadly classifiable as Double Modular Redundancy (DMR) and Triple Modular Redundancy (TMR), involving the duplication or triplication of architecture units, respectively. RISC-V plays an interesting role in this context for its inherent extendability and the availability of open-source microarchitecture designs. In this work, we present a novel way to exploit the advantages of both DMR and TMR techniques in an Interleaved-Multi-Threading (IMT) microprocessor architecture, leveraging its replicated threads for redundancy, and obtaining a system that can dynamically switch from DMR to TMR in the case of faults. We demonstrated the approach for a specific family of RISC-V cores, modifying the microarchitecture and proving its effectiveness with an extensive RTL fault-injection simulation campaign.

Over the years, significant work has been done on high-integrity systems, such as those found in cars, satellites and aircrafts, to minimize the risk that a logic fault causes a system failure, thus having functional safety as a key requirement. In this study, we employ an innovative approach to harness the benefits of both Dual Modular Redundancy and Triple Modular Redundancy techniques within an Interleaved-Multi-Threading microprocessor core, by means of a microarchitecture design capable of dynamically switching from Dual Modular Redundancy to Triple Modular Redundancy in case of faults. We explain the quantitative results obtained from an extensive fault injection simulation campaign on the fault tolerant core compared with its previous version regarding fault tolerant capabilities. The results show that in several application cases the fault resilience improvement and the hardware and timing overhead are better compared to the lockstep-based dual core approach. The proposed technique achieves 98,6% fault mitigation at the expense of only 4 clock cycles for roll-back overhead, with no checkpointing redundancy.

High-performance embedded systems with powerful processors, specialized hardware accelerators, and advanced software techniques are all key technologies driving the growth of the IoT. By combining hardware and software techniques, it is possible to increase the overall reliability and safety of these systems by designing embedded architectures that can continue to function correctly in the event of a failure or malfunction. In this work, we fully investigate the integration of a configurable hardware vector acceleration unit in the fault-tolerant RISC-V Klessydra-fT03 soft core, introducing two different redundant vector co-processors coupled with the Interleaved-Multi-Threading paradigm on which the microprocessor is based. We then illustrate the pros and cons of both approaches, comparing their impacts on performance and hardware utilization with their vulnerability, presenting a quantitative large-fault-injection simulation analysis on typical vector computing benchmarks, and comparing and classifying the obtained results. The results demonstrate, under specific conditions, that it is possible to add a hardware co-processor to a fault-tolerant microprocessor, improving performance without degrading safety and reliability.

Computing in the cloud-edge continuum, as opposed to cloud computing, relies on high performance processing on the extreme edge of the Internet of Things (IoT) hierarchy. Hardware acceleration is a mandatory solution to achieve the performance requirements, yet it can be tightly tied to particular computation kernels, even within the same application. Vector-oriented hardware acceleration has gained renewed interest to support artificial intelligence (AI) applications like convolutional networks or classification algorithms. We present a comprehensive investigation of the performance and power efficiency achievable by configurable vector acceleration subsystems, obtaining evidence of both the high potential of the proposed microarchitecture and the advantage of hardware customization in total transparency to the software program.

The low probability of single event upsets (SEU) within particular satellite orbits, makes Commercial-off-the-shelf (COTS) electronic components a viable solution for space system implementation, thanks to the introduction of design-level fault tolerance techniques at the expense of some performance/energy/area penalty. This paper illustrates the design and validation of a novel RISC-V dual-core architecture, based on a computing paradigm that we refer to as full/partial heterogeneous multi-core protection. The approach relies on a small, low-performance, fully fault-tolerant core (LP core) coupled with a high-performance partially fault-tolerant core (HP core). The computing paradigm assumes the failure-exposed HP core executes computation intensive routines for relatively short periods of time, making the occurrence of failures a statistically unlikely situation, while the fully fault-tolerant LP core operates in critical control tasks and manages the failure recovery of the high-performance core. The execution time percentage in the LP core varies from a minimum of 11.4% up to a maximum of 91.3% while in the HP core it is between 8.7% and 88.6%, depending on the application. In the proposed study, both the cores belong to the RISC-V compliant Klessydra core family. The dual-core architecture also includes a watchdog timer controlled by the LP core and monitoring the non-protected HP core, and a context switch FIFO that speeds up the code and data switch between the two cores during failure recovery. A dedicated run-time software environment coordinates the execution of tasks on the high-performance core in a resilient fashion. The dual-core processor has been validated through extensive RTL simulations running in an UVM-based fault-injection environment, which emulates SEUs at various rates. Experimental results illustrate the benefits and limits obtained by using a heterogeneous architecture with different levels of protection and performance. The failure probability assuming a SEU fault occurrence can be reduced by a factor between 10X and 30X with respect to the non-protected architecture, leading to an average failure rate of up to 4.00E-06 per second with respect to 1.80E-05 per second in the non-protected architecture.