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Brightness scaling is the most common way to reduce power consumption in OLED displays. Such “dimming” is generally static, i.e. it is applied either manually by the user, or automatically by the system in correspondence of predefined battery state-of-charge conditions. This is obviously sub-optimal, because it makes brightness adaptation (i) too coarse-grain in time, and (ii) agnostic of the image...
Off-chip serial buses are the most common interfaces between sensors and processing elements in embedded systems. Due to their length, these connections dissipate a large amount of energy, contributing significantly to the total consumption of the system. The error-tolerant feature of many sensor applications can be leveraged to reduce this energy contribution by means of an approximate serial data...
Mobile and IoT applications must balance increasing processing demands with limited power and cost budgets. Approximate computing achieves this goal leveraging the error tolerance features common in many emerging applications to reduce power consumption. In particular, adequate (i.e., energy/quality-configurable) hardware operators are key components in an error tolerant system. Existing implementations...
Organic Light Emitting Diode (OLED) display panels are becoming increasingly popular especially in mobile devices; one of the key characteristics of these panels is that their power consumption strongly depends on the displayed image.
Off-chip serial buses are common in embedded systems, and due to the long physical lines, can contribute significantly to their energy consumption. However, these buses are often connected to analog sensors, whose data is inherently affected by noise and A/D errors. Thus, communication can tolerate small approximations, without a significant impact on the system outputs quality. In this paper we propose...
Embedded computing systems include several off-chip serial links, that are typically used to interface processing elements with peripherals, such as sensors, actuators and I/O controllers. Because of the long physical lines of these connections, they can contribute significantly to the total energy consumption. On the other hand, many embedded applications are error resilient, i.e. they can tolerate...
Reduced Precision Redundancy (RPR) is a popular Approximate Computing technique, in which a circuit operated in Voltage Over-Scaling (VOS) is paired to a reduced-bitwidth and faster replica so that VOS-induced timing errors are partially recovered by the replica, and their impact is mitigated. Previous works have provided various examples of effective implementations of RPR, which however suffer from...
We present the system-level design of two accelerators for two microwave imaging algorithms for breast cancer detection. The accelerators were designed in SystemC and optimized via High-Level Synthesis (HLS). The two algorithms stress the capabilities of commercial HLS tools in different ways: the first is communication-bound and requires careful pipelining of communication and computation; the second...
In this paper we present a prototype of a Microwave Imaging (MI) system for breast cancer detection. Our system is based on low-cost off-the-shelf microwave components, custom-made antennas, and a small form-factor processing system with an embedded Field-Programmable Gate Array (FPGA) for accelerating the execution of the imaging algorithm. We show that our system can compete with a vector network...
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