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Biased-Temperature-Instability (BTI) aging mechanism reduces Static-Noise-Margin (SNM) of SRAM cells. This leads to a higher Soft-Error-Rate (SER), lower reliability, and lower SRAMs’ stability in FPGAs. SNM partially improves by leveraging the recovery phase of BTI through flipping SRAM content. We propose STABLE, a three-step post-synthesis stress-aware technique, in order to reduce the impact of BTI-induced SNM reduction in FPGA Look-up-Tables (LUTs) using the SAT-based Boolean Matching (BM) algorithm. STABLE partitions Data-Flow-Graph (DFG) of the implemented design into different cones. First, the SAT-based BM algorithm finds a new configuration for each cone while their functionalities are preserved and all SRAMs are flipped. Second, cones that did not pass the first step can benefit from unused SRAMs in their partially-used LUTs for storing the flipped configurations of such LUTs. Finally, flipped configurations of fully-used LUTs are stored in the closest unused LUTs. The main configuration of the implemented FPGA design is swapped by the new flipped configuration, periodically. Our extensive experimental analysis demonstrates 69 and 70 percent on average improvements in the SNM reduction () and the SER increase ( $\Delta SER$), respectively. Since the proposed methodology is deployed after the FPGA placement and routing of the application, the overhead is negligible. [ABSTRACT FROM PUBLISHER]

Fault-tolerant minimal routing algorithms aim at finding a Manhattan path between the source and destination nodes and route around all faulty nodes. Additionally, some non-faulty nodes that are helpless to make up of a fault-tolerant minimal path should also be routed around. How to label such non-faulty nodes efficiently is a major challenge. State-of-the-art solutions could not address it very well. We propose a path-counter method. It can label every node that are helpless to make up of a fault-tolerant minimal path with low time complexity. By counter the number of fault-tolerant minimal paths, it can: support arbitrary fault distribution, check the existence of fault-tolerant minimal paths, not sacrifice any available fault-tolerant minimal paths. [ABSTRACT FROM AUTHOR]

NoC technology is composed of packet-based interconnections, where the communication resources are distributed across the network. Therefore, the optimal resource utilization is a crucial consideration for efficient architectural designs. This paper studies the practicality of the Constraint Programming (CP) models for NoC architecture designs that effectively use a regular mesh with wormhole switching and the XY routing. The complexity of the CP models is compared with the earlier Mixed Integer Programming (MIP) models. Practical CP-based mapping and scheduling models are developed and results are reported on the benchmark datasets. Results indicate that mapping and scheduling problems can be solved at near optimality even under relatively shorter run-time limits as compared to those required by the MIP models. [ABSTRACT FROM AUTHOR]

This paper discusses heterogeneous Network-on-Chip (NoC) design from a Constraint Programming (CP) perspective and extends the formulation to solving Voltage-Frequency Island (VFI) problem. In general, VFI is a superior design alternative in terms of thermal constraints, power consumption as well as performance considerations. Given a Communication Task Graph (CTG) and subsequent task assignments for cores, cores are allocated to the best possible places on the chip in the first stage to minimize the overall communication cost among cores. We then solve the application scheduling problem to determine the optimum core types from a list of technological alternatives and to minimize the makespan. Moreover, an elegant CP model is proposed to solve VFI problem by mapping and grouping cores at the same time with scheduling the computation tasks as a limited capacity resource allocation model. The paper reports results based on real benchmark datasets from the literature. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes a novel QoS-aware and congestion-aware Network-on-Chip architecture that not only enables quality-oriented network transmission and maintains a feasible implementation cost but also well balance traffic load inside the network to enhance overall throughput. By differentiating application traffic into different service classes, bandwidth allocation is managed accordingly to fulfill QoS requirements. Incorporating with congestion control scheme which consists of dynamic arbitration and adaptive routing path selection, high priority traffic is directed to less congested areas and is given preference to available resources. Simulation results show that average latency of high priority and overall traffic is improved dramatically for various traffic patterns. Cost evaluation results also show that the proposed router architecture requires negligible cost overhead but provides better performance for both advanced mesh NoC platforms. [Copyright &y& Elsevier]

Abstract: This paper presents a high level power estimation methodology for a Network-on-Chip (NoC) router, that is capable of providing cycle accurate power profile to enable power exploration at system level. Our power macro model is based on the number of flits passing through a router as the unit of abstraction. Experimental results show that our power macro model incurs less than 5% average absolute cycle error compared to gate level analysis. The high level power macro model allows network power to be readily incorporated into simulation infrastructures, providing a fast and cycle accurate power profile, to enable power optimization such as power-aware compiler, core mapping, and scheduling techniques for CMP. As a case study, we demonstrate the use of our model for evaluating the effect of different core mappings using SPLASH-2 benchmark showing the utility of our power macro model. [Copyright &y& Elsevier]

Abstract: Although the technology scaling has enabled designers to integrate a large number of processors onto a single chip realizing chip multi-processor (CMP), problems arising from technology scaling have made power reduction an important design issue. Since interconnection networks dissipate a significant portion of the total system power budget, it is desirable to consider interconnection network''s power efficiency when designing CMP. In this paper, we present a variable frequency link for a power-aware interconnection network using the clock boosting mechanism, and apply a dynamic frequency scaling (DFS) policy, that judiciously adjusts link frequency based on link utilization parameter. Experimental result shows that history-based DFS successfully adjusts link frequency to track actual link utilization over time, demonstrating the feasibility of the proposed link as a power-aware interconnection network for system-on-chip (SoC). [Copyright &y& Elsevier]

Network-on-Chip (NoC) is a strong candidate for scalable interconnect design of Multi-Processor System-on-Chip (MPSoC). Software tasks of MPSoC require a certain protocol to communicate with each other. In NoC such a communication protocol should be handled at Network Interface and/or Processor Element level and it is expected that different protocols show their trade-offs. In consideration of the above, we employed two types of basic protocol and investigated their performance impact. The contribution of this work is to quantitatively evaluate effectiveness of using separate communication protocols depending on the task structure. [ABSTRACT FROM AUTHOR]

Abstract: There are many design challenges in the hardware-software co-design approach for performance improvement of data-intensive streaming applications with a general-purpose microprocessor and a hardware accelerator. These design challenges are mainly to prevent hardware area fragmentation to increase resource utilization, to reduce hardware reconfiguration cost and to partition and schedule the tasks between the microprocessor and the hardware accelerator efficiently for performance improvement and power savings of the applications. In this paper a modular and block based hardware configuration architecture named memory-aware run-time reconfigurable embedded system (MARTRES) is proposed for efficient resource management and performance improvement of streaming applications. Subsequently we design a task placement algorithm named hierarchical best fit ascending (HBFA) algorithm to prove that MARTRES configuration architecture is very efficient in increased resource utilization and flexible in task mapping and power savings. The time complexity of HBFA algorithm is reduced to O(n) compared to traditional Best Fit (BF) algorithm’s time complexity of O(n 2), when the quality of the placement solution by HBFA is better than that of BF algorithm. Finally we design an efficient task partitioning and scheduling algorithm named balanced partitioned and placement-aware partitioning and scheduling algorithm (BPASA). In BPASA we exploit the temporal parallelism in streaming applications to reduce reconfiguration cost of the hardware, while keeping in mind the required throughput of the output data. We balance the exploitation of spatial parallelism and temporal parallelism in streaming applications by considering the reconfiguration cost vs. the data transfer cost. The scheduler refers to the HBFA placement algorithm to check whether contiguous area on FPGA is available before scheduling the task for HW or for SW. [Copyright &y& Elsevier]

Sorting, which is widely used in different areas such as database systems, IP routing, bio informatics, and cognitive-processing-based applications, imposes considerable overhead on computing resources. Therefore, an efficient on-chip sorting accelerator may significantly enhance real-time decision-making in such applications. In this paper we introduce a novel pipelined and parallel sorting algorithm with streaming I/O, with the time, logic, and memory complexity of , , and , respectively. We present a formal analysis to prove the correctness of this algorithm. We then model, verify, and synthesize this unconditional algorithm (in the TSMC 0.13 micron technology) for 4k-word clusters as an ASIC accelerating engine. More specifically, our implementation with 3969-word multiple-bank memory, 63 word-size comparators, 64 word-size multiplexers, and 63 word-size registers only requires some 8k clock cycles to sort an arbitrary 3969-word long array of random data, which arrive at the sorter and also depart it one item at a time. [Copyright &y& Elsevier]

Discusses problems faced with packings and embeddings of hypercubes into n-dimensional star graphs. Detailed information on packings, embeddings, and related definitions; Information on the template multiple-sized packings; Indepth look at variable-dilation embeddings (VDEs); Other related information on packings and embeddings of hypercubes.

Introduces the software-protection methods against piracy. Goals of software authorization system; Ways in implementing the system; Application of copy protection in enabling unauthorized person to obtain a copy of a program.

Deep neural networks (DNNs) have been employed to different devices as a popular machine learning algorithm (ML) owing to deploy the Internet of Things (IoT), data mining in cloud computing, and web search engines, which MLs had an impressive effect on IoT's edge level nodes. Deploying DNN-based applications leads to memory access problems, including communication delay, energy efficiency, and bandwidth requirement. We propose a bus scheduling for data placement on distributed local buffers in a deep learning accelerator (DLA). The contributions of this paper include (1) providing a method for data-flow mapping between off-chip DRAM and distributed local buffers, and a flow mapping approach for data transfer between distributed local buffers and processing elements (PEs) (2) employing distributed local buffers in four directions for traffic distribution on a mesh based on memory access mechanism (3) bus scheduling for data placement on distributed local buffers. Simulated experiment based on typical DNN (i.e., AlexNet, VGG-16, and GoogLeNet) workflows demonstrates the effectiveness of the design: (1) the scheduling and mapping methods improve total runtime and bandwidth requirement by approximately 42.29% and 88.95% compared with TPU, respectively. Additionally, (2) our methods reduce total runtime for row-column stationary plus by approximately 99% compared with weight-stationary data-flow in CONV1 and CONV11 of VGG-16, respectively. This work reports the simulation results based on distributing AlexNet, VGG-16, and GoogLeNet's traffics as the popular CNNs and DNNs models, whereas it investigates our method's efficiency for other trained models. [ABSTRACT FROM AUTHOR]

Convolutional neural networks have been proposed as an approach for classifying data corresponding to a variety of datasets. Indeed, developments in data diversity and information technology have increased the complexity of deep learning algorithms. Numerous trained models have been proposed for supporting complex algorithms and data detachment with high accuracy. Convolutional operations increase when the convolution depth of neural networks increases. Thus, employing deep convolutional networks is challenging regarding energy consumption, bandwidth, memory requirements, and memory access. Different types of on-chip communication platforms and traffic distribution methods are effective in the improvement of memory access and energy consumption induced by data transfer. Also, dataflow mapping methods have an impressive effect on reducing or increasing delay and energy consumption caused by exchanging data between cores of a communication network. Different methods have been proposed to dataflow mapping on various networks for reducing total hop counts that led to improve performance and cost. Dataflow mapping approach can affect performance improvement of the inference phase in neural networks. This paper proposes various traffic patterns by considering different memory access mechanisms for traffic distribution of a trained AlexNet model on mesh topology. We propose a flow mapping method (FMM) on the mesh to determine the data flow efficiency of different traffic patterns on energy consumption. The FMM reduced energy and total flow by approximately 17.86% and 34.16%, respectively, using different traffic patterns. Thus, the FMM improved the performance of AlexNet traffic distribution while the impact on data flow reduced energy consumption. [ABSTRACT FROM AUTHOR]

While 3-D integrated circuits (ICs) offer many advantages over 2-D ICs, thermal management challenges remain unresolved. Thermal through-silicon-vias (TTSVs) are TSVs that facilitate heat transfer across stacked dies without carrying signal and provide a potential thermal management solution to 3-D ICs. However, the use of TTSVs increases the distance between IC blocks and signal delay. The trade-off between temperature and wirelength is difficult to avoid in TTSV-integrated 3-D ICs. Here, we present a hierarchical approach to optimize the floorplan of a 3-D Nehalem-based multicore processor via simulated annealing (SA). Our simulations show that an increase in the TTSV area accompanies a decrease in peak temperature but the wirelength strongly depends on the TTSV placement, which is uniquely optimized for each case of the allowed TTSV area. Compared to the floorplan with a fixed TTSV placement that places TTSV between cores, our algorithm optimally places TTSVs between IC blocks and finds an optimal floorplan with the minimum cost of peak temperature, wirelength, and area at 6% TTSV area overhead. The peak temperature is reduced from 116 °C to 100 °C with only a 3.5% increase in wirelength. Our floorplan optimization method can provide effective thermal management solutions to 3-D ICs. [ABSTRACT FROM AUTHOR]

Multiple memory stacks can be integrated with a processor chip in the silicon interposer technology ("2.5D" stacking). In 2.5D architecture, there are two different network layers for both coherence and memory traffic. The CPU layer is used for coherence Core-to-Core traffic, while the interposer layer is associated with Core-to-Memory blocks traffic regularly. A load balancing strategy balances the traffics on the two network layers and optimizes the resources utilization. In the aforementioned strategy, after detecting congestion in the CPU layer, packets can be moved to the interposer one. It can be concluded that this transferring encounters the bottleneck of the edge portion that is connected to memory blocks. In this paper, we propose a Controlled Load Balancing Mechanism (CLBM) which efficiently controls bottleneck in load balancing methods. As a result, the CLBM selects an appropriate network based on the destination address without comparing latencies of two networks. Moreover, a multicast fault-tolerant ring is introduced to propagate network congestion information. The experimental results showed that, as compared with the absence of load balancing method and traditional load balancing strategy, our CLBM strategy achieves 37.82% and 17.22% average latency improvements and 22.19% and 8.55% average total power with minor overhead. [ABSTRACT FROM AUTHOR]

Selection strategy is an essential part of an adaptive routing algorithm that influences the performance of the networks‐on‐chip (NoC). A selection strategy is used for selecting the best output channel from the available channels according to the network status. This study presents a new output selection strategy called destination intensity and congestion aware (DICA) that uses both local and regional congestion information from adjacent and two hops away neighbours on the path to destination based on the channel and switch information. Also, the proposed output selection strategy uses a new global congestion‐aware scheme based on destination node called destination congestion awareness method to distribute traffic more equally over the network. The simulation results show that DICA strategy consistently improves the performance in both throughput and average latency with minimal overhead in terms of area consumption for various synthetic and real application traffic patterns. In addition, the microarchitecture of NoC routers is also presented in this study and it shows that the proposed output selection strategy can be combined with any adaptive routing algorithms. The experimental results show the average delay improvements of DICA to the Bufferlevel, neighbours‐on‐path, and regional congestion awareness are 87, 57, and 24%, respectively. [ABSTRACT FROM AUTHOR]

Highlights • BC-NoC is an efficient method to reduce network packet latency. • Proposed RIP BC-NoC partitioning method enhances workload consolidation density. • Task communication minimally uses other application resources. • Application tasks can be mapped close to each other in a straight path. • Increased consolidation density & reduced latency improve performance parameters. Abstract The network on a chip (NoC) is considered as the main shared communication resource to avoid compromise the system performance. A strict isolation strategy is employed in the NoC to avoid performance degradation; however, this strategy is accompanied by a low consolidation density or a complex routing mechanism, which leads to considerable latency and high hardware costs. We propose the row irregular partitioning (RIP) method, which results in a high consolidation density compared to regularity-oriented topology. We additionally propose a congestion awareness (CA) mapping scheme in which mapping is performed based on congestion control on a route in a bypass-channel-based NoC (BC-NoC). Furthermore, mapping methods, such as straight path (SP) and straight path and congestion awareness (SP&CA), are recommended to exploit the communication platform properties of BC-NoC. The experimental results show that the average delay in the SP mapping method is improved compared with SP&CA and CA. [ABSTRACT FROM AUTHOR]

Three dimensional Networks-on-Chip (3D NoCs) have evolved as an ideal solution to the communication demands and complexity of future high density many core architectures. However, the design practicality of 3D NoCs faces several challenges such as thermal issues, high power consumption and area overhead of 3D routers as well as high complexity and cost of vertical link implementation. To mitigate the performance and manufacturing cost of 3D NoCs, inhomogeneous architectures have emerged to combine 2D and 3D routers in 3D NoCs producing lower area and energy consumption while maintaining the performance of homogeneous 3D NoCs. Due to the limited number of vertical links, application mapping on inhomogeneous 3D NoCs can be complex. However, application mapping has a great impact on the performance and energy consumption of NoCs. This paper presents an energy and performance aware application mapping algorithm for inhomogeneous 3D NoCs. The algorithm has been evaluated with various realistic traffic patterns and compared with existing mapping algorithms. Experimental results show NoCs mapped with the proposed algorithm have lower energy consumption and significant reduction in packet delays compared to the existing algorithms and comparable average packet latency with Branch-and-Bound. [ABSTRACT FROM AUTHOR]

In this paper, we propose an energy-efficient reconfigurable platform for in-memory processing based on novel four-terminal spin Hall effect-driven domain wall motion devices that could be employed as both nonvolatile memory cell and in-memory logic unit. The proposed designs lead to unity of memory and logic. The device to system level simulation results show that, with 28% area increase in memory structure, the proposed in-memory processing platform achieves a write energy ~15.6 fJ/bit with 79% reduction compared to that of SOT-MRAM counterpart while keeping the identical 1 ns writing speed. In addition, the proposed in-memory logic scheme improves the operating energy by 61.3%, as compared with the recent nonvolatile in-memory logic designs. An extensive reliability analysis is also performed over the proposed circuits. We employ advanced encryption standard (AES) algorithm as a case study to elucidate the efficiency of the proposed platform at application level. Simulation results exhibit that the proposed platform can show up to 75.7% and 30.4% lower energy consumption compared to CMOS-ASIC and recent pipelined domain wall (DW) AES implementations, respectively. In addition, the AES energy-delay product can show 15.1% and 6.1% improvements compared to the DW-AES and CMOS-ASIC implementations, respectively. [ABSTRACT FROM AUTHOR]

The movement toward 3D fabrication coupled with Network-on-Chip (NoC) aims to improve area, performance, power, and scalability of many-core systems. However, reliability issue as a perpetual challenge in advanced silicon technology imperils it. Aging is an emerging reliability concern, which degrades the system's performance and causes timing failure eventually. Bias-Temperature-Instability (BTI) and Hot-Carrier-Injection (HCI) are the dominant aging mechanisms, which escalate in high temperature and stress (i.e., usage). In addition to the intra-layer temperature variations, 3D NoCs experience inter-layer temperature variations, which demand necessary investigations for aging as compared to 2D NoC. In this paper, we propose AROMa, an aging-aware deadlock-free adaptive routing algorithm integrated with a novel online aging monitoring system for 3D NoCs. The monitoring system in AROMa exploits Distributed-Centralized-Aging-Table (D-CAT) to obtain routers’ aging rates for each layer of 3D NoCs periodically. Consequently, AROMa swaps between different k-best source-destination shortest paths periodically to avoid highly aged routers, force them in recovery phase of BTI, and accordingly balance aging in the network. We prove that AROMa is deadlock free. Our extensive experimental analysis using gem5 full system mode for PARSEC and SPLASH-2 benchmark suites concludes that AROMa outperforms state-of-the-art works while improving age imbalance by 70 percent and maximum age by 35 percent in 3D NoC with negligible overheads. [ABSTRACT FROM AUTHOR]

In the movement from a multi‐core to a many‐core era, cores count on the chip increases quickly thus interconnect plays a large role in achieving the desired performance. Network‐on‐chip (NoC) is the most widely used interconnect as a scalable alternative for traditional shared bus in many‐core chips. As the dimensions of mesh‐based NoC increase, routers and links serve as a major part to achieve the desired performance and low‐latency communication between cores. In this study, the authors propose an arbitration mechanism for NoC that leads to a reduction in congestion delay in routers as well as the network latency. The proposed mechanism is compatible with the bypass and baseline pipeline in routers. System simulations with Noxim demonstrate reduction in latencies and power consumption using different routing algorithms for 4×4,8×8 and 16×16 mesh topologies, as compared with a baseline router. [ABSTRACT FROM AUTHOR]

Recently, Through-Silicon-Via (TSV) has been more popular to provide faster inter-layer communication in three-dimensional Networks-on-Chip (3D NoCs). However, the area overhead of TSVs reduces wafer utilization and yield which impact design of 3D architectures using a large number of TSVs such as homogeneous 3D NoCs topologies. Also, 3D routers require more memory and thus they are more power hungry than conventional 2D routers. Alternatively, hybrid 3D NoCs combine both the area and performance benefits of 2D and 3D router architectures by using a limited number of TSVs. Existing hybrid architectures suffer from higher packet delays as they do not consider the dynamic communication patterns of different application and their NoC resource usage. We propose a novel algorithm to systematically generate hybrid 3D NoC topologies for a given application such that the vertical connections are minimized while the NoC performance is not sacrificed. The proposed algorithm analyses the target application and generates hybrid architectures by efficiently redistributing the vertical links and buffer spaces based on their utilizations. Furthermore, the algorithm has been evaluated with synthetic and various real-world traffic patterns. Experimental results show that the proposed algorithm generates optimized architectures with lower energy consumption and a significant reduction in packet delay compared to the existing solutions. [ABSTRACT FROM PUBLISHER]

Reliability is one of the most challenging problems in the context of three-dimensional network-on-chip (3D NoC) systems. Reliability analysis is prominent for early stages of the manufacturing process in order to prevent costly redesigns of a target system. This article classifies the potential physical faults of a baseline TSV-based 3D NoC architecture by targeting two-dimensional (2D) NoC components and their inter-die connections. In this paper, through-silicon via (TSV) issues, thermal concerns, and single event effect (SEE) are investigated and categorized, in order to propose evaluation metrics for inspecting the resiliency of 3D NoC designs. A reliability analysis for major source of faults is reported in this article separately based on their mean time to failure (MTTF). TSV failure probability induced by inductive and capacitive coupling is also discussed. Finally, the paper provides a formal reliability analysis on the aggregated faults that affect TSV. This formal analysis is critical for estimating the resiliency of different components in order to mitigate the redundancy cost of fault-tolerant design or to examine the efficiency of any proposed fault-tolerant methods for 3D NoC architectures. [ABSTRACT FROM PUBLISHER]

Network-on-chip (NoC) architecture is regarded as a solution for future on-chip interconnects. However, the performance advantages of conventional NoC architectures are limited by the long latency and high power consumption due to multi-hop long-distance communication among processing elements. To solve these limitations, we employed on-chip wireless communication as express links for transferring data so that transfer latency can be reduced. A hybrid NoC architecture utilizing both wired and wireless communication approaches is proposed in this paper. We also devised a deadlock-free routing algorithm that is able to make efficient use of the incorporated wireless links. Moreover, simulated annealing optimization techniques were applied to find optimal locations for wireless routers. Cycle-accurate simulation results showed a significant improvement in transfer latency. Area and power consumption analysis demonstrates the feasibility of our proposed NoC architecture. [ABSTRACT FROM AUTHOR]

Efficient on-chip communication is necessary for exploiting enormous computing power available on a many-core chip. Routing algorithms play a major role for the communication quality and performance of the on-chip interconnection networks. This paper proposes TagNoC, as an on-chip network router architecture with novel hybrid routing approach which reduces latency and power consumption at a fixed cost based on information redundancy. TagNoC is a hybrid routing approach which combines the source and distributed routing methods together. While eliminating packet routing in each router, TagNoC determines the forwarding output port in parallel with input buffering. For a marginal cost increase in header size, as compared to distributed routing techniques, routing latency can be hidden while eliminating power consuming portion of the routing, increasing router throughput and decreasing latency. The proposed TagNoC router is compared to baseline router with distributed routing implementation on a 16-node CMP mesh. Physical implementation of all routers is modeled using synthesized RTL, detailed area analysis, and accurate channel models. Performance evaluation is also carried out utilizing RTL simulation and detailed power analysis on both synthetic and application traffic is performed using post-synthesis gate-level simulation. The simulation results illustrate that TagNoC outperforms as compared to baseline distributed architecture and other source routing methods in terms of power, latency, and throughput. [ABSTRACT FROM AUTHOR]

Abstract: Adaptive routing algorithms have been employed in interconnection networks to improve network throughput and provide better fault tolerance characteristics. However, they can harm performance by disturbing any inherent global load balance through greedy local decisions. This paper proposes a novel scalable load balancing congestion-aware Network-on-Chip (NoC) architecture that not only enhances network transmission performance while maintaining a feasible implementation cost, but also improves overall network throughput for various traffic scenarios. This congestion control scheme which consists of dynamic input arbitration and adaptive routing path selection is proposed to balance global traffic load distribution so as to alleviate congestion caused by heavy network activities. Furthermore, faulty links information can be broadcasted by existing congestion management control signals to prevent packets from routing through defected areas in order to eliminate potential heavy congestion situations around these regions. Experimental results show that throughput is improved dramatically while maintaining superior latency performance for various traffic patterns. Compared to a baseline router, the proposed congestion management mechanism requires negligible cost overhead but provides better throughput for both mesh and diagonally-linked mesh NoC platforms. [Copyright &y& Elsevier]

Network‐on‐chip (NoC) performance largely depends on the underlying deadlock‐free and efficient routing algorithm. The effectiveness of any adaptive routing algorithm strongly depends on the underlying selection strategy. When the routing function returns a set of admissible output channels with cardinality greater than one, a selection function is used to select the output channel to which the packet will be forwarded. In this study a novel selection strategy, LATEX, is proposed that can be used with any adaptive routing algorithm for specified applications. The objective of the proposed selection strategy is to efficiently balance traffic load and reach better performance results. Performance evaluation is carried out by using a flit‐accurate simulator under two real traffic scenarios. Result experiments show that the proposed selection strategy applied to several routing algorithms significantly improves average delay, max delay and power consumption. [ABSTRACT FROM AUTHOR]

Abstract: Integration of hundreds of processors on a chip will become practical thanks to ultra-deep submicron VLSI technology. As wiring delay becomes a bottleneck for a scalable design, on-chip interconnects turn into the critical issues for system performance and reliability. To mitigate long wiring delay impact, wireless on-chip communication infrastructures featuring hybrid mechanisms exploiting both wired and wireless communications have been proposed. By shortening long distance transmission latency and lowering wired network overhead, overall system transfer latency and energy dissipation are improved accordingly. However, unbalanced traffic management reduces the benefit of high speed wireless links so that wired networks also degrade accordingly. To extract the best performance for these hybrid networks, an intelligent congestion-aware router design is needed to balance traffic load and eliminate congestion delay. A sophisticated routing scheme accommodating more throughput and featuring light weight congestion-aware mechanism which uses the number of blocking buffers as a guideline to avoid serious congestion was designed and evaluated. Modified 7-port routers achieve better performance and the proposed routing algorithm successfully eliminates congestion scenarios and efficiently balances traffic loads. This is the first work to exchange congestion information locally and globally to improve network utilization and transmission quality. The experimental results showed significant improvement in transfer latency, network throughput and power efficiency with moderate hardware cost overhead. [Copyright &y& Elsevier]

We propose a lightweight scheme where the formation of a data block is changed in such a way that it can tolerate soft errors significantly better than the baseline. The key insight behind our work is that CNN weights are normalized between -1 and 1 after each convolutional layer, and this leaves one bit unused in half-precision floating-point representation. By taking advantage of the unused bit, we create a backup for the most significant bit to protect it against the soft errors. Also, considering the fact that in MLC STT-RAMs the cost of memory operations (read and write), and reliability of a cell are content-dependent (some patterns take larger current and longer time, while they are more susceptible to soft error), we rearrange the data block to minimize the number of costly bit patterns. Combining these two techniques provides the same level of accuracy compared to an error-free baseline while improving the read and write energy by 9% and 6%, respectively. [ABSTRACT FROM AUTHOR]

Silent Data Corruptions (SDCs), those errors that escape detection methods, are critical for system designers because they may result in systems failures. In order to catch SDCs, mechanisms should focus on the behavioural aspects of errors in addition to their physical location or error patterns. Therefore, protection codes like parity, hamming, and the Reed-Solomon code, which heavily depend on the physical location of data bits, are not enough in processors for detection of computing errors. Using characterizing data behaviour during program executions, we have observed value locality in results of destination register for each instruction binary code (instruction opcode and operand codes). This locality exists not only in the results of each instruction, but also in the results of instructions at different memory locations having the same binary code. As a result, an architecture called Instruction Result History Table (IRHT) is presented, which is indexed by the instruction binary code. In the IRHT, a history of values produced by the same instruction binary codes are stored in and utilized during each instruction execution cycle. Any mismatch between the stored values in the IRHT and those generated by current execution, indicates an SDC syndrome. To confirm having SDCs with a high level of confidence, a second execution of the current instruction is issued. A duplication of the execution confirms whether SDC occurred. In the case of SDCs, a third instruction execution with the help of a majority voting frees the system of SDC. Several extensive simulations showed that, up to 83.54% of SDCs are detectable with the help of this locality. Moreover, with the small hardware, IRHT, i.e., 16 kB size, 80.66% of SDCs can be detected on average. Note that the presented method can detect those errors that escape conventional detection mechanisms. So, it can be utilized in conjunction with other conventional methods. [ABSTRACT FROM AUTHOR]

Deep neural networks are widely used in many artificial intelligence applications. They have demonstrated state-of-the-art accuracy on many artificial intelligence tasks. For this high accuracy to occur, deep neural networks require the right parameter values. This is achieved by a process known as training. The training of large amounts of data via many iterations comes at a high cost in regard to computation time and energy. Optimal resource allocation would therefore reduce the training time. TensorFlow, a computational graph library developed by Google, alleviates the development of neural network models and provides the means to train these networks. In this article, we propose Adaptive HTF-MPR to carry out the resource allocation, or mapping, on TensorFlow. Adaptive HTF-MPR searches for the best mapping in a hybrid approach. We applied the proposed methodology on two well-known image classifiers: VGG-16 and AlexNet. We also performed a full analysis of the solution space of MNIST Softmax. Our results demonstrate that Adaptive HTF-MPR outperforms the default homogeneous TensorFlow mapping. In addition to the speed up, Adaptive HTF-MPR can react to changes in the state of the system and adjust to an improved mapping. [ABSTRACT FROM AUTHOR]

Spin transfer torque magnetic random access memory (STT-MRAM) is a promising candidate for next generation memory as it is non-volatile, fast, and has unlimited endurance. Another important aspect of STT-MRAM is that its core component, the nanoscale magnetic tunneling junction (MTJ), is thought to be radiation hard, making it attractive for space and nuclear technology applications. However, studies on the effects of ionizing radiation on the STT-MRAM writing process are lacking for MTJs with perpendicular magnetic anisotropy (pMTJs) required for scalable applications. Particularly, the question of the impact of extreme total ionizing dose on perpendicular magnetic anisotropy, which plays a crucial role on thermal stability and critical writing current, remains open. Here we report measurements of the impact of high doses of gamma and neutron radiation on nanoscale pMTJs used in STT-MRAM. We characterize the tunneling magnetoresistance, the magnetic field switching, and the current-induced switching before and after irradiation. Our results demonstrate that all these key properties of nanoscale MTJs relevant to STT-MRAM applications are robust against ionizing radiation. Additionally, we perform experiments on thermally driven stochastic switching in the gamma ray environment. These results indicate that nanoscale MTJs are promising building blocks for radiation-hard non-von Neumann computing. [ABSTRACT FROM AUTHOR]

The magnesium oxide (MgO) adhesion layer is proposed to avoid adverse effects of lossy metallic adhesion layers in thin film plasmonic nanostructures. Such adverse effects can be in the form of resonance broadening and a decrease in the resonance magnitude. We fabricate and test the quality of MgO adhesion layers and determine its optical properties through ellipsometry measurements. We also provide the plasmonic response of various plasmonic nanostructures (nanohole array, nanodisk array, dimer nanohole array, and bowtie slot antenna array) with a MgO adhesion layer and conventional adhesion layers including titanium (Ti), chromium (Cr), tantalum (Ta), and indium tin oxide (ITO). Our results show that unlike conventional adhesives, MgO has almost no adverse effect on the plasmonic resonance of the designed nanostructures. [ABSTRACT FROM AUTHOR]

The balanced ternary representation allows for significant performance improvement for ternary systems. Immaturity of the semiconductor industry in providing an applicable device for ternary infrastructures during the past decades is an enormous obstacle to actualize the ternary circuit realization. Among the promising devices for this purpose, carbon nanotube field effect transistor (CNFET) is qualified with outstanding characteristics which make it suitable for implementing the ternary logic functions. In this paper, for the first time, we present and evaluate the basic ternary arithmetic circuits in balanced representation based on the CNFET technology. Experimental evaluation of reviewed designs in both balanced and unbalanced representation indicates the superiority of the balanced representation in the design of ternary arithmetic blocks. [ABSTRACT FROM AUTHOR]

This paper proposes energy-efficient approximate multipliers based on the Mitchell's log multiplication, optimized for performing inferences on convolutional neural networks (CNN). Various design techniques are applied to the log multiplier, including a fully-parallel LOD, efficient shift amount calculation, and exact zero computation. Additionally, the truncation of the operands is studied to create the customizable log multiplier that further reduces energy consumption. The paper also proposes using the one's complements to handle negative numbers, as an approximation of the two's complements that had been used in the prior works. The viability of the proposed designs is supported by the detailed formal analysis as well as the experimental results on CNNs. The experiments also provide insights into the effect of approximate multiplication in CNNs, identifying the importance of minimizing the range of error.The proposed customizable design at $w$w = 8 saves up to 88 percent energy compared to the exact fixed-point multiplier at 32 bits with just a performance degradation of 0.2 percent for the ImageNet ILSVRC2012 dataset. [ABSTRACT FROM AUTHOR]

Quantum dot cellular automata (QCA) is one of the nano-scale computing paradigms which promises high speed and ultra-low power consumption. Since the one-bit full adder is a fundamental building block of arithmetic circuits, designing an efficient QCA full adder cell is very imperative in this new technology. In this paper, we propose a QCA full adder using a new inverter gate which leads to reduced complexity and area occupation. The proposed layout is simulated by the QCA designer engines. We also provide a performance comparison of our proposed QCA full adder with the previous relevant designs. Furthermore, a detailed analysis of energy dissipation is performed which demonstrates the superiority of the proposed design in terms of the energy efficiency. [ABSTRACT FROM AUTHOR]

3D integration opens up new opportunities for future multiprocessor chips by enabling fast and highly scalable 3D Network-on-Chip (NoC) topologies. However, in an aim to reduce the cost of Through-silicon via (TSV), partially vertically connected NoCs, in which only a few vertical TSV links are available, have been gaining relevance. To reliably route packets under such conditions, we introduce a lightweight, efficient and highly resilient adaptive routing algorithm targeting partially vertically connected 3D-NoCs named First-Last. It requires a very low number of virtual channels (VCs) to achieve deadlock-freedom (2 VCs in the East and North directions and 1 VC in all other directions), and guarantees packet delivery as long as one healthy TSV connecting all layers is available anywhere in the network. An improved version of our algorithm, named Enhanced-First-Last is also introduced and shown to dramatically improve performance under low TSV availability while still using less virtual channels than state-of-the-art algorithms. A comprehensive evaluation of the cost and performance of our algorithms is performed to demonstrate their merits with respects to existing solutions. [ABSTRACT FROM AUTHOR]

2D-NoCs have been the mainstream approach used to interconnect multi-core systems. 3D-NoCs have emerged to compensate for deficiencies of 2D-NoCs such as long latency and power overhead. A low-latency routing algorithm for 3D-NoC is designed to accommodate high-speed communication between cores. Both simulation and analytical models are applied to estimate the communication latency of NoCs. Generally, simulations are time-consuming and slow down the design process. Analytical models provide, within a fraction of the time, nearly accurate results which can be used by simulation to fine-tune the design. In this paper, a high performance and adaptive routing algorithm has been proposed for partially connected 3D-NoCs. Latency of the routing algorithm under different traffic patterns, different number of elevators and different elevator assignment mechanisms are reported. An analytical model, tailored to the adaptivity of the algorithm and under low traffic scenarios, has been developed and the results have been verified by simulation. According to the results, simulation and analytical results are consistent within a 10 percent margin. [ABSTRACT FROM AUTHOR]

In modern many-core architectures, advanced on-chip networks provide the means of communication for the cores. This greatly complicates the design and verification of the cache coherence protocols deployed by those cores. A common approach to deal with this complexity is to decompose the whole system into the protocol and the network. This decomposition is, however, not always possible. For example, unexpected deadlocks can emerge when a deadlock-free protocol and a deadlock-free network are combined. This paper proposes a compositional methodology: prove properties over a network, prove properties over a protocol, and infer properties over the system as a whole. Our methodology is based on theorems that show that such decomposition is possible by having sufficiently large local buffers at the cores. We apply this methodology to verify several protocols such as MI, MSI, MESI and MEUSI running on top of advanced interconnects with adaptive routing. [ABSTRACT FROM AUTHOR]

Backgrounds: Nowadays developing smart and fast services for patients and transforming hospitals to modern hospitals is considered a necessity. Living in the world inundated with information systems, designing services based on information technology entails a suitable architecture framework.Objectives: This paper aims to present a localized enterprise architecture framework for the Iranian university hospital.Methods and Results: Using two dimensions of implementation and having appropriate characteristics, the best 17 enterprises frameworks were chosen. As part of this effort, five criteria were selected according to experts' inputs. According to these criteria, five frameworks which had the highest rank were chosen. Then 44 general characteristics were extracted from the existing 17 frameworks after careful studying. Then a questionnaire was written accordingly to distinguish the necessity of those characteristics using expert's opinions and Delphi method. The result showed eight important criteria. In the next step, using AHP method, TOGAF was chosen regarding having appropriate characteristics and the ability to be implemented among reference formats. In the next step, enterprise architecture framework was designed by TOGAF in a conceptual model and its layers. For determining architecture framework parts, a questionnaire with 145 questions was written based on literature review and expert's opinions. The results showed during localization of TOGAF for Iran, 111 of 145 parts were chosen and certified to be used in the hospital.Conclusion: The results showed that TOGAF could be suitable for use in the hospital. So, a localized Hospital Enterprise Architecture Modelling is developed by customizing TOGAF for an Iranian hospital at eight levels and 11 parts. This new model could be used to be performed in other Iranian hospitals. [ABSTRACT FROM AUTHOR]

This paper presents two new ternary operators which can be used in different scrambling crypto algorithms. The employment of the proposed operators ( ScramOp1 and ScramOp2 ) leads to reduction in the number of decoding steps, equivalent to only one operation per digit for the receiver side. These operators are presented for the first time in ternary logic. There are some other ternary operators such as SUM , which are specifically suitable for computer arithmetic but they lack desirable efficiency for cryptographic applications. The transistor-level designs of the operators are simulated by using Synopsys HSPICE with 32 nm bulk-CMOS technology. Simulation results demonstrate that ScramOp1 and ScramOp2 achieve significant saving in energy consumption (2.11% and 12.14%) in comparison with SUM . Additionally, ScramOp2 requires only 52 transistors while 58 and 60 transistors are needed to implement ScramOp1 and SUM , respectively. [ABSTRACT FROM AUTHOR]

This paper proposes a highly scalable sensor design for late transition detection in FPGA based platforms. Transition delays occur because of aging mechanisms such as Biased Temperature Instability (BTI) and Hot Carrier Injection (HCI). We propose a sensor clock (SCLK) that is a function of minimum slack time of a set of paths selected for age monitoring. There will be one such clock for many sensors as are needed in an entire FPGA. Our proposed sensor architecture makes it possible for a single SCLK to be shared by all sensors. Additionally, the proposed sensor occupies one slice (basic FPGA logic block), which leads to low area, power, and performance overhead. Using Artix-7-based board, experimental results demonstrate that the proposed aging sensor detects aging earlier than existing sensors and provides less power and performance overheads. [ABSTRACT FROM AUTHOR]