Precision-aware Latency and Energy Balancing on Multi-Accelerator Platforms for DNN Inference

The need to execute Deep Neural Networks (DNNs) at low latency and low power at the edge has spurred the development of new heterogeneous Systems-on-Chips (SoCs) encapsulating a diverse set of hardware accelerators. How to optimally map a DNN onto such multi-accelerator systems is an open problem. We propose ODiMO, a hardware-aware tool that performs a fine-grain mapping across different accelerators on-chip, splitting individual layers and executing them in parallel, to reduce inference energy consumption or latency, while taking into account each accelerator's quantization precision to maintain accuracy. Pareto-optimal networks in the accuracy vs. energy or latency space are pursued for three popular dataset/DNN pairs, and deployed on the DIANA heterogeneous ultra-low power edge AI SoC. We show that ODiMO reduces energy/latency by up to 33%/31% with limited accuracy drop (-0.53%/-0.32%) compared to manual heuristic mappings

A Survey on Reconfigurable System-on-Chips

The requirements for high performance and low power consumption are becoming more and more inevitable when designing modern embedded systems, especially for the next generation multi-mode multimedia or communication standards. Ultra large-scale integration reconfigurable System-on-Chips (SoCs) have been proposed to achieve not only better performance and lower energy consumption but also higher flexibility and versatility in comparison with the conventional architectures. The unique characteristic of such systems is integration of many types of heterogeneous reconfigurable processing fabrics based on a Network-on-Chip. This paper analyzes and emphasizes the key research trends of the reconfigurable System-on-Chips (SoCs). Firstly, the emerging hardware architecture of SoCs is highlighted. Afterwards, the key issues of designing the reconfigurable SoCs are discussed, with the focus on the challenges when designing reconfigurable hardware fabrics and reconfigurable Network-on-Chips. Finally, some state-of-the-art reconfigurable SoCs are briefly discussed

Evaluating Cache Coherent Shared Virtual Memory for Heterogeneous Multicore Chips

The trend in industry is towards heterogeneous multicore processors (HMCs), including chips with CPUs and massively-threaded throughput-oriented processors (MTTOPs) such as GPUs. Although current homogeneous chips tightly couple the cores with cache-coherent shared virtual memory (CCSVM), this is not the communication paradigm used by any current HMC. In this paper, we present a CCSVM design for a CPU/MTTOP chip, as well as an extension of the pthreads programming model, called xthreads, for programming this HMC. Our goal is to evaluate the potential performance benefits of tightly coupling heterogeneous cores with CCSVM

Channel Characterization for Chip-scale Wireless Communications within Computing Packages

Wireless Network-on-Chip (WNoC) appears as a promising alternative to conventional interconnect fabrics for chip-scale communications. WNoC takes advantage of an overlaid network composed by a set of millimeter-wave antennas to reduce latency and increase throughput in the communication between cores. Similarly, wireless inter-chip communication has been also proposed to improve the information transfer between processors, memory, and accelerators in multi-chip settings. However, the wireless channel remains largely unknown in both scenarios, especially in the presence of realistic chip packages. This work addresses the issue by accurately modeling flip-chip packages and investigating the propagation both its interior and its surroundings. Through parametric studies, package configurations that minimize path loss are obtained and the trade-offs observed when applying such optimizations are discussed. Single-chip and multi-chip architectures are compared in terms of the path loss exponent, confirming that the amount of bulk silicon found in the pathway between transmitter and receiver is the main determinant of losses.Comment: To be presented 12th IEEE/ACM International Symposium on Networks-on-Chip (NOCS 2018); Torino, Italy; October 201

CMOS-3D smart imager architectures for feature detection

This paper reports a multi-layered smart image sensor architecture for feature extraction based on detection of interest points. The architecture is conceived for 3-D integrated circuit technologies consisting of two layers (tiers) plus memory. The top tier includes sensing and processing circuitry aimed to perform Gaussian filtering and generate Gaussian pyramids in fully concurrent way. The circuitry in this tier operates in mixed-signal domain. It embeds in-pixel correlated double sampling, a switched-capacitor network for Gaussian pyramid generation, analog memories and a comparator for in-pixel analog-to-digital conversion. This tier can be further split into two for improved resolution; one containing the sensors and another containing a capacitor per sensor plus the mixed-signal processing circuitry. Regarding the bottom tier, it embeds digital circuitry entitled for the calculation of Harris, Hessian, and difference-of-Gaussian detectors. The overall system can hence be configured by the user to detect interest points by using the algorithm out of these three better suited to practical applications. The paper describes the different kind of algorithms featured and the circuitry employed at top and bottom tiers. The Gaussian pyramid is implemented with a switched-capacitor network in less than 50 μs, outperforming more conventional solutions.Xunta de Galicia 10PXIB206037PRMinisterio de Ciencia e Innovación TEC2009-12686, IPT-2011-1625-430000Office of Naval Research N00014111031

An Energy-Efficient Reconfigurable Circuit Switched Network-on-Chip

Network-on-Chip (NoC) is an energy-efficient on-chip communication architecture for multi-tile System-on-Chip (SoC) architectures. The SoC architecture, including its run-time software, can replace inflexible ASICs for future ambient systems. These ambient systems have to be flexible as well as energy-efficient. To find an energy-efficient solution for the communication network we analyze three wireless applications. Based on their communication requirements we observe that revisiting of the circuit switching techniques is beneficial. In this paper we propose a new energy-efficient reconfigurable circuit-switched Network-on-Chip. By physically separating the concurrent data streams we reduce the overall energy consumption. The circuit-switched router has been synthesized and analyzed for its power consumption in 0.13 ¿m technology. A 5-port circuit-switched router has an area of 0.05 mm2 and runs at 1075 MHz. The proposed architecture consumes 3.5 times less energy compared to its packet-switched equivalen