In this paper, we present the new FPGA EMUlation (FEMU), an open-source and configurable emulation framework for prototyping and evaluating TinyAI heterogeneous systems (HS). FEMU leverages the capability of system-on-chip (SoC)-based FPGAs to combine the under-development HS implemented in a reconfigurable hardware region (RH) for quick prototyping with a software environment running under a standard operating system in a control software region (CS) for supervision and communication. To evaluate our approach, we built the X-HEEP FPGA EMUlation (X-HEEP-FEMU) platform by instantiating the proposed framework with real-world hardware and software components. X-HEEP-FEMU is deployed on the Xilinx Zynq-7020 SoC and integrates the eXtendible Heterogeneous Energy Efficient Platform (X-HEEP) host in the RH, a Linux-based Python environment on the ARM Cortex-A9 CS, and energy models derived from a TSMC 65 nm CMOS silicon implementation of X-HEEP, called HEEPocrates.

Coarse-Grain Reconfigurable Arrays (CGRAs) represent emerging low-power architectures designed to accelerate Compute-Intensive Loops (CILs). The effectiveness of CGRAs in providing acceleration relies on the quality of mapping: how efficiently the CIL is compiled onto the platform. State-of-the-Art (SoA) compilation techniques utilize modulo scheduling to minimize the Iteration Interval (II) and use graph algorithms like Max-Clique Enumeration to address mapping challenges. Our work approaches the mapping problem through a satisfiability (SAT) formulation. We introduce the Kernel Mobility Schedule (KMS), an ad hoc schedule used with the Data Flow Graph and CGRA architectural information to generate Boolean statements that, when satisfied, yield a valid mapping. Experimental results demonstrate SAT-MapIt outperforming SoA alternatives in almost 50% of explored benchmarks. Additionally, we evaluated the mapping results in a synthesizable CGRA design and emphasized the runtime metrics trends, i.e., energy efficiency and latency, across different CILs and CGRA sizes. We show that a hardware-agnostic analysis performed on compiler-level metrics can optimally prune the architectural design space, while still retaining Pareto-optimal configurations. Moreover, by exploring how implementation details impact cost and performance on real hardware, we highlight the importance of holistic software-to-hardware mapping flows, as the one presented herein.

In this work, we propose an open-hardware low-power coarse-grained reconfigurable array connected to a lightweight microcontroller and enclosed in an application mapping framework. The latter provides complete support to configure kernels in the reconfigurable array, execute applications, and measure performance.

X-HEEP (eXtendable Heterogeneous Energy-Efficient Platform) is an open-source1, configurable, and extensible single-core RISC-V microcontroller developed at the Embedded Systems Laboratory (ESL) of EPFL for edge-computing platforms. X-HEEP can be used standalone as a low-cost microcontroller, or it can be integrated into existing platforms to act like a peripheral subsystem, or it can be extended and customized with external peripherals and accelerators nimbly. The latter is particularly appealing for novel accelerators, memories, or peripherals designers who desire a simple controller to drive their IP and communicate with the external world using software functions. X-HEEP is built on top of existing, mature open-source IPs such as CPUs, peripherals, and many other building blocks from the OpenHW Group, the PULP team from ETH Zurich and the University of Bologna, and lowRISC. Its contribution includes its expandability, configurability, and agile use, targetting a large number of users to take one step further towards the democratization of open-source hardware.

Sea surface salinity can be measured by microwave radiometry at L-band (1400-1427 MHz). This frequency is a compromise between sensitivity to the salinity, small atmospheric perturbation, and reasonable pixel resolution. The description of the ocean emission depends on two main factors: (1) the sea water permittivity, which is a function of salinity, temperature, and frequency, and (2) the sea surface state, which depends on the wind-induced wave spectrum, swell, and rain-induced roughness spectrum, and by the foam coverage and its emissivity. This study presents a simplified two-layer emission model for foam-covered water and the results of a controlled experiment to measure the foam emissivity as a function of salinity, foam thickness, incidence angle, and polarization. Experimental results are presented, and then compared to the two-layer foam emission model with the measured foam parameters used as input model parameters. At 37 psu salt water the foam-induced emissivity increase is /spl sim/0.007 per millimeter of foam thickness (extrapolated to nadir), increasing with increasing incidence angles at vertical polarization, and decreasing with increasing incidence angles at horizontal polarization.