Temperature Evaluation of NoC Architectures and Dynamically Reconfigurable NoC

Advancements in the field of chip fabrication led to the integration of a large number of transistors in a small area, giving rise to the multi–core processor era. Massive multi–core processors facilitate innovation and research in the field of healthcare, defense, entertainment, meteorology and many others. Reduction in chip area and increase in the number of on–chip cores is accompanied by power and temperature issues. In high performance multi–core chips, power and heat are predominant constraints. High performance massive multicore systems suffer from thermal hotspots, exacerbating the problem of reliability in deep submicron technologies. High power consumption not only increases the chip temperature but also jeopardizes the integrity of the system. Hence, there is a need to explore holistic power and thermal optimization and management strategies for massive on–chip multi–core environments. In multi–core environments, the communication fabric plays a major role in deciding the efficiency of the system. In multi–core processor chips this communication infrastructure is predominantly a Network–on–Chip (NoC). Tradition NoC designs incorporate planar interconnects as a result these NoCs have long, multi–hop wireline links for data exchange. Due to the presence of multi–hop planar links such NoC architectures fall prey to high latency, significant power dissipation and temperature hotspots. Networks inspired from nature are envisioned as an enabling technology to achieve highly efficient and low power NoC designs. Adopting wireless technology in such architectures enhance their performance. Placement of wireless interconnects (WIs) alters the behavior of the network and hence a random deployment of WIs may not result in a thermally optimal solution. In such scenarios, the WIs being highly efficient would attract high traffic densities resulting in thermal hotspots. Hence, the location and utilization of the wireless links is a key factor in obtaining a thermal optimal highly efficient Network–on–chip. Optimization of the NoC framework alone is incapable of addressing the effects due to the runtime dynamics of the system. Minimal paths solely optimized for performance in the network may lead to excessive utilization of certain NoC components leading to thermal hotspots. Hence, architectural innovation in conjunction with suitable power and thermal management strategies is the key for designing high performance and energy–efficient multicore systems. This work contributes at exploring various wired and wireless NoC architectures that achieve best trade–offs between temperature, performance and energy–efficiency. It further proposes an adaptive routing scheme which factors in the thermal profile of the chip. The proposed routing mechanism dynamically reacts to the thermal profile of the chip and takes measures to avoid thermal hotspots, achieving a thermally efficient dynamically reconfigurable network on chip architecture

Energy Efficient Network-on-Chip Architectures for Many-Core Near-Threshold Computing System

Near threshold computing has unraveled a promising design space for energy efficient computing. However, it is still plagued by sub-optimal system performance. Application characteristics and hardware non-idealities of conventional architectures (those optimized for nominal voltage) prevent us from fully leveraging the potential of NTC systems. Increasing the computational core count still forms the bedrock of a multitude of contemporary works that address the problem of performance degradation in NTC systems. However, these works do not categorically address the shortcomings of the conventional on-chip interconnect fabric in a many core environment. In this work, we quantitatively demonstrate the performance bottleneck created by a conventional NTC architecture in many-core NTC systems. To reclaim the performance lost due to a sub-optimal NoC in many-core NTC systems, we propose BoostNoC—a power efficient, multi-layered network-on-chip architecture. BoostNoC improves the system performance by nearly 2× over a conventional NTC system, while largely sustaining its energy benefits. Further, capitalizing on the application characteristics, we propose two BoostNoC derivative designs: (i) PG BoostNoC; and (ii) Drowsy BoostNoC; to improve the energy efficiency by 1.4× and 1.37×, respectively over conventional NTC system

Dynamic Energy Management for Chip Multi-processors under Performance Constraints

We introduce a novel algorithm for dynamic energy management (DEM) under performance constraints in chip multi-processors (CMPs). Using the novel concept of delayed instructions count, performance loss estimations are calculated at the end of each control period for each core. In addition, a Kalman filtering based approach is employed to predict workload in the next control period for which voltage-frequency pairs must be selected. This selection is done with a novel dynamic voltage and frequency scaling (DVFS) algorithm whose objective is to reduce energy consumption but without degrading performance beyond the user set threshold. Using our customized Sniper based CMP system simulation framework, we demonstrate the effectiveness of the proposed algorithm for a variety of benchmarks for 16 core and 64 core network-on-chip based CMP architectures. Simulation results show consistent energy savings across the board. We present our work as an investigation of the tradeoff between the achievable energy reduction via DVFS when predictions are done using the effective Kalman filter for different performance penalty thresholds