Physically Unclonable Functions (PUFs) are security primitives that provide trustworthy hardware for key-generation and device authentication. Among them, in contrast to dedicated PUFs, intrinsic PUFs are created from existing hardware components that exploit their variability through software. In this work we focus on GPUs and present G-PUF, a PUF implemented entirely in software on CUDA and hence does not require hardware modifications. Our results show that G-PUF has comparable characteristics to SRAM and DRAM PUFs in terms of uniformity 55.61% and reliability 90.09%.

Embedded processors must efficiently deliver performance at low energy consumption. Both configurable and reconfigurable techniques can be used to fulfill such constraints, although applied in different situations. In this work, we propose DIM-VEX, a configurable processor coupled with a reconfigurable fabric, which can leverage both design time configurability and runtime reconfigurability. We show that, on average, such system can improve performance by up to 1.41X and reduce energy by up to 60% when compared to a configurable processor at the cost of additional area.

Many modern FPGA-based soft-processor designs must include dedicated hardware modules to satisfy the requirements of a wide range of applications. Not seldom they all do not fit in the FPGA target, so their functionalities must be mapped into the much slower software domain. However, many complex soft-core processors usually underuse the available Block RAMs (BRAMs) when comparing to LUTs and registers. By taking advantage of this fact, we propose a generic low-cost BRAM-based function reuse mechanism (the BRAM-FR) that can be easily configured for precise or approximate modes to accelerate execution. The BRAM-FR was implemented in HDL and coupled to a configurable 4-issue VLIW processor. It was used to optimize different applications that use a soft-float library to emulate a Floating-Point Unit (FPU), and an image processing filter that tolerates a certain level of error. We show that our technique can accelerate the former by 1.23x and the latter by 1.52x, with a Reuse Table that fits in the BRAMs (that would otherwise be idle) of five tested FPGA targets with a marginal increase in the number of slice registers and LUTs.

Software-based methods for the detection of control-flow errors caused by transient fault usually consist in the introduction of protecting instructions both at the beginning and at the end of basic blocks. These methods are conservative in nature, in the sense that they assume that all blocks have the same probability of being the target of control flow errors. Because of that assumption they can lead to a considerable increase both in memory and performance overhead during execution time. In this paper, we propose a static analysis that provide a more refined information about which basic blocks can be the target of control-flow-errors caused by single-bit flips. This information can then be used to guide a program transformation in which only susceptible blocks have to be protected. We implemented the static analysis and program transformation in the context of the LLVM framework and performed an extensive fault injection campaign. Our experiments show that this less conservative approach can potentially lead to gains both in memory usage and in execution time while keeping high fault coverage.

In this tutorial we discuss the impact of multicore architectures for embedded devices at different levels, ranging from heterogeneous/homogeneous ISAs to the organization and software development.