Providing an Adaptive Routing along with a Hybrid Selection Strategy to Increase Efficiency in NoC-Based Neuromorphic Systems

Effective and efficient routing is one of the most important parts of routing in NoC-based neuromorphic systems. In fact, this communication structure connects different units through the packets routed by routers and switches embedded in the network on a chip. With the help of this capability, not only high scalability and high development can be created, but by decreasing the global wiring to the chip level, power consumption can be reduced. In this paper, an adaptive routing algorithm for NoC-based neuromorphic systems is proposed along with a hybrid selection strategy. Accordingly, a traffic analyzer is first used to determine the type of local or nonlocal traffic depending on the number of hops. Then, considering the type of traffic, the RCA and NoP selection strategies are used for the nonlocal and local strategies, respectively. Finally, using the experiments that performed in the simulator environment, it has been shown that this solution can well reduce the average delay time and power consumption.

Increasing brain palmitoylation rescues behavior and neuropathology in Huntington disease mice

Huntington disease (HD) damages the corticostriatal circuitry in large part by impairing transport of brain-derived neurotrophic factor (BDNF). We hypothesized that improving vesicular transport of BDNF could slow or prevent disease progression. We therefore performed selective proteomic analysis of vesicles transported within corticostriatal projecting neurons followed by in silico screening and identified palmitoylation as a pathway that could restore defective huntingtin-dependent trafficking. Using a synchronized trafficking assay and an HD network-on-a-chip, we found that increasing brain palmitoylation via ML348, which inhibits the palmitate-removing enzyme acyl-protein thioesterase 1 (APT1), restores axonal transport, synapse homeostasis, and survival signaling to wild-type levels without toxicity. In human HD induced pluripotent stem cell–derived cortical neurons, ML348 increased BDNF trafficking. In HD knock-in mice, it efficiently crossed the blood-brain barrier to restore palmitoylation levels and reverse neuropathology, locomotor deficits, and anxio-depressive behaviors. APT1 and its inhibitor ML348 thus hold therapeutic interest for HD.

Network-on-a-chip of a new microprocessor generation with the Elbrus architecture

The paper describes a network-on-chip of a new microprocessor generation with the Elbrus architecture, taking into account the peculiarities of physical design. The network-on-a-chip under consideration plays a central role in the scaling process of the microprocessor, interconnecting all the main components of the system and ensuring the transfer of all types of packets between devices. The characteristics of the network-on-a-chip determine the bandwidth and access time to the memory subsystem.

A Network Adaptive Fault-Tolerant Routing Algorithm for Demanding Latency and Throughput Applications of Network-on-a-Chip Designs

Scalability is a significant issue in system-on-a-chip architectures because of the rapid increase in numerous on-chip resources. Moreover, hybrid processing elements demand diverse communication requirements, which system-on-a-chip architectures are unable to handle gracefully. Network-on-a-chip architectures have been proposed to address the scalability, contention, reusability, and congestion-related problems of current system-on-a-chip architectures. The reliability appears to be a challenging aspect of network-on-a-chip architectures because of the physical faults introduced in post-manufacturing processes. Therefore, to overcome such failures in network-on-a-chip architectures, fault-tolerant routing is critical. In this article, a network adaptive fault-tolerant routing algorithm is proposed, where the proposed algorithm enhances an efficient dynamic and adaptive routing algorithm. The proposed algorithm avoids livelocks because of its ability to select an alternate outport. It also manages to bypass congested regions of the network and balances the traffic load between outports that have an equal number of hop counts to its destination. Simulation results verified that in a fault-free scenario, the proposed solution outperformed a fault-tolerant XY by achieving a lower latency. At the same time, it attained a higher flit delivery ratio compared to the efficient dynamic and adaptive routing algorithm. Meanwhile, in the situation of a faulty network, the proposed algorithm could reach a higher flit delivery ratio of up to 18% while still consuming less power compared to the efficient dynamic and adaptive routing algorithm.

Presynaptic APP levels and synaptic homeostasis are regulated by Akt phosphorylation of huntingtin

Studies have suggested that amyloid precursor protein (APP) regulates synaptic homeostasis, but the evidence has not been consistent. In particular, signaling pathways controlling APP transport to the synapse in axons and dendrites remain to be identified. Having previously shown that Huntingtin (HTT), the scaffolding protein involved in Huntington’s disease, regulates neuritic transport of APP, we used a microfluidic corticocortical neuronal network-on-a-chip to examine APP transport and localization to the pre- and post-synaptic compartments. We found that HTT, upon phosphorylation by the Ser/Thr kinase Akt, regulates APP transport in axons but not dendrites. Expression of an unphosphorylatable HTT decreased axonal anterograde transport of APP, reduced presynaptic APP levels, and increased synaptic density. Ablating in vivo HTT phosphorylation in APPPS1 mice, which overexpress APP, reduced presynaptic APP levels, restored synapse number and improved learning and memory. The Akt-HTT pathway and axonal transport of APP thus regulate APP presynaptic levels and synapse homeostasis.

Presynaptic APP levels and synaptic homeostasis are regulated by Akt phosphorylation of Huntingtin

Studies have suggested that amyloid precursor protein (APP) regulates synaptic homeostasis, but the evidence has not been consistent. In particular, signaling pathways controlling APP transport to the synapse in axons and dendrites remain to be identified. Having previously shown that Huntingtin (HTT), the scaffolding protein involved in Huntington’s disease, regulates neuritic transport of APP, we used a microfluidic corticocortical neuronal network-on-a-chip to examine APP transport and localization to the pre- and post-synaptic compartments. We found that HTT, upon phosphorylation by the Ser/Thr kinase Akt, regulates APP transport in axons but not dendrites. Expression of an unphosphorylatable HTT decreased axonal anterograde transport of APP, reduced presynaptic APP levels, and increased synaptic density. Ablating in vivo HTT phosphorylation in APPPS1 mice, which overexpress APP, reduced presynaptic APP levels, restored synapse number and improved learning and memory. The Akt-HTT pathway and axonal transport of APP thus regulate APP presynaptic levels and synapse homeostasis.

Adaptive Time-Triggered Multi-Core Architecture

The static resource allocation in time-triggered systems offers significant benefits for the safety arguments of dependable systems. However, adaptation is a key factor for energy efficiency and fault recovery in Cyber-Physical System (CPS). This paper introduces the Adaptive Time-Triggered Multi-Core Architecture (ATMA), which supports adaptation using multi-schedule graphs while preserving the key properties of time-triggered systems including implicit synchronization, temporal predictability and avoidance of resource conflicts. ATMA is an overall architecture for safety-critical CPS based on a network-on-a-chip with building blocks for context agreement and adaptation. Context information is established in a globally consistent manner, providing the foundation for the temporally aligned switching of schedules in the network interfaces. A meta-scheduling algorithm computes schedule graphs and avoids state explosion with reconvergence horizons for events. For each tile, the relevant part of the schedule graph is efficiently stored using difference encodings and interpreted by the adaptation logic. The architecture was evaluated using an FPGA-based implementation and example scenarios employing adaptation for improved energy efficiency. The evaluation demonstrated the benefits of adaptation while showing the overhead and the trade-off between the degree of adaptation and the memory consumption for multi-schedule graphs.