Area Budget Research Articles

Spatial Correlation of Land Use Carbon Budget Based on Social Network Analysis： A Case Study of Chongqing Metropolitan Area

Clarifying the temporal and spatial changes in the carbon budget in the Chongqing metropolitan area and exploring the spatial correlation of land use carbon budget are of great significance for realizing the regional "double carbon" goal. Using 21 districts and counties in Chongqing metropolitan area as the research scale, the IPCC inventory method, carbon emission coefficient method, Gini coefficient, gravity model, and social network analysis were used to estimate the net carbon emissions from land use in Chongqing metropolitan area from 2000 to 2020, and the spatial correlation of the carbon budget was obtained. The results revealed that： ① In the past 20 years, the carbon budget of the Chongqing metropolitan area showed an overall upward trend, with an average annual growth rate of 2.83%, and the spatial distribution was "higher in the north and south, higher in the east and west, and lower in the middle." ② During the past 20 years, the spatial difference of net carbon emissions in the Chongqing metropolitan area became highly average, and the overall Gini coefficient decreased by 11.42%, whereas the intra-group difference was the largest in key development zones. ③ In the past 20 years, the overall structure of the spatial correlation network of land use carbon budget in the Chongqing metropolitan area has become stable and complex, and the network density and network correlation number have increased by 0.43 and 180, respectively, the network correlation degree has increased to 1, and the network health degree has improved. ④ In the individual network structure of land use carbon budget in the Chongqing metropolitan area, the degree centrality of each district and county has increased, and the increase in the central urban area was the most significant, with an increase of 81, whereas the decline in intermediate centrality and proximity centrality has promoted the regional coordinated development and integration process in the metropolitan area. ⑤ In the past 20 years, the density of net carbon emissions in the Chongqing metropolitan area has increased as a whole, with the density of the core area increasing by 0.35 and the density of the core-edge area increasing by 0.34. By exploring the change and spatial correlation of land use carbon budget in the Chongqing metropolitan area, this study clarified the spatial distribution difference of carbon budget and provided support for regional green development.

Evaluating the effectiveness of protected area management in Indonesia

Abstract Protected areas worldwide are strongholds for safeguarding biodiversity, natural habitats, ecosystem services and cultural values. Yet despite their importance, the effectiveness of protected area management varies greatly. Indonesia is a biodiversity hotspot, with 554 protected areas that cover 27 million ha across the archipelago. To assess and improve the management effectiveness of these protected areas, the Government of Indonesia applied an adapted version of the Management Effectiveness Tracking Tool (METT) to assess 422 of the country's protected areas, of which 170 were repeatedly assessed in 2015, 2017 and 2019. We investigated the METT score changes across these protected areas and the factors explaining the varying scores. Over the study years, METT scores significantly improved (mean increase of 44.1%). National parks had the highest mean score, which was 13.4 points higher than other protected area types. After correcting for spatial autocorrelation using a generalized least-squares model, we found that METT score increase was positively influenced by year of assessment and having a well-resourced management authority, with no influence of protected area size or mean protected area budget allocation per ha. The assessments identified five main threats to protected areas: poaching, illegal logging, human settlements, tourism and non-timber cultivation. The widespread and repeated use of METT across the protected areas of Indonesia and the increasing METT scores indicate an overall improvement in management and professionalism. Building on the foundational work in our study, future studies should assess the association between METT scores and progress made towards achieving the conservation objectives of protected areas.

Statistical Analysis of Climate Trends and Impacts on Groundwater Sustainability in the Lower Indus Basin

Agricultural intensification is increasing global demand for water, with groundwater especially susceptible given its year-round reliability. Climate change impacts on groundwater recharge exacerbate uncertainties for future access and use, especially for large aquifers across alluvial plains such as the Indus Basin of Pakistan. To generate better understanding of climate change impacts on groundwater balances in such contexts, we used MODFLOW 2005 to quantify the groundwater budget of the Northern Rohri Canal Command Area under RCP 4.5 and 8.5 climatic scenarios, while also taking climatic regionalisation into account. Under a baseline scenario, total annual pumping in the northern Rohri command was estimated to be 3.619 billion cubic metres (BCM), and the total net loss in storage over the simulation period from October 2010 to April 2014 was estimated at 1.244 BCM per year. By 2047, net decline in storage is projected to more than double to 2.185 per year under RCP 4.5 scenario and 2.214 under RCP 8.5. Our estimates suggest that a sustainable yield across the command area should be managed at approximately 3 ± 0.3 BCM per year to ensure sufficient adaptive reserves of groundwater for access during times of drought and inadequate surface supply, while also reducing waterlogging impacts from high watertables. This first-time estimate of sustainable yield provides irrigation system managers with an overall guide from which divisional-scale measures to achieve the goal can be identified through stakeholder engagement.

Desmonte da política de inovação: estratégias e causas no Brasil contemporâneo

Abstract This paper analyzes the policy dismantling process in the Brazilian innovation system since mid-2010. The research describes how this policy change has been undertaken and explains the strategies deployed and major causes. The study is theoretically grounded in the debate of policy dismantling, meaning changes that result in cuts, reductions, or even abolition of budget, rules, capacities, and instruments of a governmental area. A mixed-methods approach, both quantitative and qualitative, is employed. First, it examines the dismantling process in the last years, focusing on the budget execution patterns of the major policy instruments and agencies in charge of innovation at the federal level. The research relies on the stakeholders’ perception by conducting semi-structured interviews with experts regarding strategies, rationale, reactions, and effects. The empirical findings show the dismantling occurs in both dimensions: density (number of tools reduced) and, mainly, the intensity (budget cuts), varying according to government areas. The interviewees highlighted the prevailing strategy as active dismantling, in which the fiscal austerity aggravated by the COVID-19 crisis, an ideological shift in the government coalition, policy particularities, and a low level of prioritization in innovation by the domestic business community are the main factors that affect the politicians’ preferences to dismantle. Finally, the process seriously affects the national innovation system, such as the loss of bureaucratic and policy capacity, brain drain, and lag in technology, productivity, and consequently, in the country’s economic performance.

The Stepwise Reduction of Multiyear Sea Ice Area in the Arctic Ocean Since 1980

AbstractThe loss of multiyear sea ice (MYI) in the Arctic Ocean is a significant change that affects all facets of the Arctic environment. Using a Lagrangian ice age product, we examine MYI loss and quantify the annual MYI area budget from 1980 to 2021 as the balance of export, melt, and replenishment. Overall, MYI area declined at 72,500 km2/yr; however, a majority of the loss occurred during two stepwise reductions that interrupt an otherwise balanced budget and resulted in the northward contraction of the MYI pack. First, in 1989, a change in atmospheric forcing led to a +56% anomaly in MYI export through Fram Strait. The second occurred from 2006 to 2008 with anomalously high melt (+25%) and export (+23%) coupled with low replenishment (−8%). In terms of trends, melt has increased since 1989, particularly in the Beaufort Sea, export has decreased since 2008 due to reduced MYI coverage north of Fram Strait, and replenishment has increased over the full time series due to a negative feedback that promotes seasonal ice survival at higher latitudes exposed by MYI loss. However, retention of older MYI has significantly declined, transitioning the MYI pack toward younger MYI that is less resilient than previously anticipated and could soon elicit another stepwise reduction. We speculate that future MYI loss will be driven by increased melt and reduced replenishment, both of which are enhanced with continued warming and will one day render the Arctic Ocean free of MYI, a change that will coincide with a seasonally ice‐free Arctic Ocean.

Comparable early-stage decomposition but contrasting underlying drivers between surface and cave habitats along an elevational gradient

Decomposition is a major contributor to ecosystem respiration, determining the carbon emission and nutrient cycling rates. Our current understanding of decomposition dynamics and their underlying drivers has mainly focused on surface habitats but largely ignored in subterranean environments. Here we studied abiotic and microbial drivers of early-stage litter decomposition inside and outside caves along an elevational gradient in Tenerife. We found comparable decomposition rates (k) and litter stabilizing factors (S), with contrasting drivers and elevational variation. At the surface, we observed a mid-elevational trend in k, which tended to correlate with water availability, cooler temperatures, nutrient availability, and surface-specific bacterial taxa. In sharp contrast, caves showed no elevational impact nor influence of abiotic parameters and bacterial communities on k. Despite this, we found higher levels of S in caves, which were associated mainly with reduced water availability, lower temperatures and cave-specific bacterial taxa, indicating that conditions in caves are strongly linked with carbon storage. Our findings imply that our current perception of terrestrial habitat-based carbon cycling are underestimating the net carbon budget in areas with caves. Disentangling the role of the environment on decomposition in caves is key to fully characterize their roles in nutrient cycling and to understand how increasing anthropogenic pressures will affect fundamental processes in subterranean ecosystems.

Improving land-cover-based expert matrices to quantify the dynamics of ecosystem service supply, demand, and budget: Optimization of weight distribution

Although the land-cover-based expert matrices have been widely used for ecosystem service assessment, criticisms about the accuracy and reliability of this method have never ceased. In this study, we introduced a weight distribution approach called Full Permutation Polygon Synthetic Indicator (FPPSI) into the land-cover-based expert matrices, trying to reduce the systemic flaws caused by the default weight assignment and accumulative calculation form of general matrices method. Taking Hangzhou, a representative city in the rapid urbanization process of China as an example, we used the weight optimization expert matrices to quantify the dynamics of ecosystem service supply, demand, and budget during the period of dramatic land cover change from 1990 to 2020. An indicator named supply–demand balanced index (SDBI) was formulated to describe the supply–demand situation among ecosystem services. The results indicated that with the continuous encroachment of the artificial surface on suburban cultivated land, the supply and demand of the 12 selected ecosystem services had experienced a decreasing trend in varying degrees. The evaluation results derived from the general method indicated that the ecosystem service budget of the study area had dropped by an average of 11.1% in the past 30 years, while the percentage was only 5.7% through the weight optimization method. Through literature review and discussion, we note that ecosystem services assessment is a process fraught with uncertainty. The weight optimization method has the advantage of being convenient, intuitive, and adjustable. It can also export more conservative evaluation results compared with the general method, which can better reflect the dynamic and non-linear process between land use types and ecosystem services to a certain extent. The above findings provide new insights for reducing uncertainty in land-cover-based expert matrices assessments, which can be applied to the practical assessment of ecosystem supply and demand with dramatic land use/land cover changes.

Trireme: Exploration of Hierarchical Multi-level Parallelism for Hardware Acceleration

The design of heterogeneous systems that include domain specific accelerators is a challenging and time-consuming process. While taking into account area constraints, designers must decide which parts of an application to accelerate in hardware and which to leave in software. Moreover, applications in domains such as Extended Reality (XR) offer opportunities for various forms of parallel execution, including loop level, task level, and pipeline parallelism. To assist the design process and expose every possible level of parallelism, we present Trireme , a fully automated tool-chain that explores multiple levels of parallelism and produces domain-specific accelerator designs and configurations that maximize performance, given an area budget. FPGA SoCs were used as target platforms, and Catapult HLS [ 7 ] was used to synthesize RTL using a commercial 12 nm FinFET technology. Experiments on demanding benchmarks from the XR domain revealed a speedup of up to 20×, as well as a speedup of up to 37× for smaller applications, compared to software-only implementations.

Water Vapor Budget Features and Its Precipitation Effects over the Key Area of Sichuan-Tibet Railway in Summer

In this study, we investigate the variation of characteristics of summer precipitation with different magnitudes and the water vapor budget in different key areas of the Sichuan-Tibet Railway by using the daily precipitation data from meteorological stations and the monthly mean ERA-Interim reanalysis data from 1979 to 2018. The results show that the summer heavy precipitation anomaly in the Brahmaputra valley and mountain (BVM) area is generated by the multi-scale interactions between the unique topography and different water vapor transports at low latitudes. When an intense anticyclonic circulation occurs over the western Pacific and the South China Sea, there is also an anomalous anticyclonic circulation extending from the northern Indian Peninsula to the Bay of Bengal. This circulation pattern is conductive to the increase of the water vapor inflow from the southern boundary and the net water vapor budget in the BVM area. The strong southwesterly wind and water vapor convergence over this area thus leading to heavy precipitation in the summer. The summer heavy precipitation amount, frequency and intensity in the western parts of the steep terrain (ST) area on the east slope of the plateau are positively correlated with the water vapor inflow from its western boundary. However, the correlations of the water vapor budget to the summer heavy precipitation amount and frequency are opposite in the eastern parts of the ST area. The unique terrain and circulation patterns lead to the localization and diversity of heavy precipitation in the ST area.

HyGain: High-performance, Energy-efficient Hybrid Gain Cell-based Cache Hierarchy

In this article, we propose a “full-stack” solution to designing high-apacity and low-latency on-chip cache hierarchies by starting at the circuit level of the hardware design stack. We propose a novel half V DD precharge 2T Gain Cell (GC) design for the cache hierarchy. The GC has several desirable characteristics, including ~50% higher storage density and ~50% lower dynamic energy as compared to the traditional 6T SRAM, even after accounting for peripheral circuit overheads. We also demonstrate data retention time of 350 us (~17.5× of eDRAM) at 28 nm technology with V DD = 0.9V and temperature = 27°C that, combined with optimizations like staggered refresh, makes it an ideal candidate to architect all levels of on-chip caches. We show that compared to 6T SRAM, for a given area budget, GC-based caches, on average, provide 30% and 36% increase in IPC for single- and multi-programmed workloads, respectively, on contemporary workloads, including SPEC CPU 2017. We also observe dynamic energy savings of 42% and 34% for single- and multi-programmed workloads, respectively. Finally, in a quest to utilize the best of all worlds, we combine GC with STT-RAM to create hybrid hierarchies. We show that a hybrid hierarchy with GC caches at L1 and L2 and an LLC split between GC and STT-RAM is able to provide a 46% benefit in energy-delay product (EDP) as compared to an all-SRAM design, and 13% as compared to an all-GC cache hierarchy, averaged across multi-programmed workloads.

Early DSE and Automatic Generation of Coarse-grained Merged Accelerators

Post-Moore’s law area-constrained systems rely on accelerators to deliver performance enhancements. Coarse-grained accelerators can offer substantial domain acceleration, but manual, ad hoc identification of code to accelerate is prohibitively expensive. Because cycle-accurate simulators and high-level synthesis (HLS) flows are so time-consuming, the manual creation of high-utilization accelerators that exploit control and data flow patterns at optimal granularities is rarely successful. To address these challenges, we present AccelMerger, the first automated methodology to create coarse-grained, control- and data-flow-rich merged accelerators. AccelMerger uses sequence alignment matching to recognize similar function call-graphs and loops, and neural networks to quickly evaluate their post-HLS characteristics. It accurately identifies which functions to accelerate, and it merges accelerators to respect an area budget and to accommodate system communication characteristics like latency and bandwidth. Merging two accelerators can save as much as 99% of the area of one. The space saved is used by a globally optimal integer linear program to allocate more accelerators for increased performance. We demonstrate AccelMerger’s effectiveness using HLS flows without any manual effort to fine-tune the resulting designs. On FPGA-based systems, AccelMerger yields application performance improvements of up to 16.7× over software implementations, and 1.91× on average with respect to state-of-the-art early-stage design space exploration tools.

Design, Analysis and Optimization of Magnetic-Core Solenoid Inductor for On-Chip Multi-Phase Buck Converter

Due to heterogeneous integration, there is an increased demand for on-chip DC-DC converters to provide multiple voltage domains for efficient operation of the system. Towards this, planar magnetic-core based inductors gained popularity due to their increased inductance density for on-chip buck converter realization. To ensure proper operation of the converter, the magnetic-core should not saturate, and over-design of the inductor decreases the converter efficiency significantly. Also, the magnetic-core area budget is limited for on-chip design. This paper proposes an optimization framework to design an efficient multi-phase buck converter with the magnetic-core solenoid inductor for the given specifications. We investigate two cost-functions for optimization where Cost function <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> considers only power loss reduction, whereas Cost function <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> considers both power loss and inductor footprint. Full-wave simulations on commercial tool show that the optimized multi-phase buck converter with 500 mA load current achieves 88.13% and 88.06% efficiency for Cost function <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> and Cost function <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , respectively. The footprint for the optimized inductor with Cost function <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> has a 10% reduction compared with the optimized inductor with Cost function <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> .

Factors affecting the radon (222Rn) emanation from aquifer rock materials: Implications for radiological and groundwater tracer studies

Groundwater discharge (GD) is an important component of the water budget in large urban areas with high water demands. Radon is a routinely used groundwater tracer in mass-balances for evaluating GD to surface water bodies. The diffusion of 222Rn from aquifers' sediments parameter is important for GD's assessments. Sediment equilibration experiments were employed with various sediment and rock materials, including sand, granite, gneiss and loess that constitute the Pampeano Aquifer (PA) in the Buenos Aires Province, Argentina. These experiments allowed the 222Rn concentration determination in pore fluids at secular equilibrium and to examine the factors affecting the magnitude of radon 222Rn emanation from the materials under study. We found that radon emanation decreases in a power function (R2 = 0.9, n = 6) with the particle size of the tested PA sediment and rock materials. Based on our results, loess sediments with the smallest particle size and the largest particle surface area have the highest radon emanation. This strongly suggests that these two parameters are the parameters that govern the radon diffusive fluxes' magnitude in the PA. On the other hand, we found that PA basement rocks, primarily granite and gneiss, showed an exhalation rate of radon of 8.1 ± 0.81 Bq∙m−2∙h−1 and 13.2 ± 1.32 Bq∙m−2∙h−1. These rates are two orders of magnitude higher than loess sediments (0.3 ± 0.1 Bq∙m−2∙h−1), owning to the higher natural content of radon's parent isotopes from the 238U natural decay series. These high radon levels are consistent with currently available radon concentrations measured in groundwater in contact with the PA basement rock formations. This study demonstrates the importance of considering site-specific aquifer properties in the radon diffusive fluxes when utilizing radon as a groundwater tracer in hydrological studies. This is the first quantitative study that examines the aquifer characteristics affecting radon emanations in this large hydrogeological system.

AxRLWE: A Multilevel Approximate Ring-LWE Co-Processor for Lightweight IoT Applications

This work presents a multilevel approximation exploration undertaken on the Ring-Learning-with-Errors (R-LWE)-based public-key cryptographic (PKC) schemes that belong to quantum-resilient cryptography algorithms. Among the various quantum-resilient cryptography schemes proposed in the currently running NIST’s post-quantum cryptography (PQC) standardization plan, the lattice-based learning-with-error (LWE) schemes have emerged as the most viable and preferred class for the Internet of Things (IoT) applications due to their compact area and memory footprint compared to other alternatives. However, compared to the classical schemes used today, R-LWE is much harder a challenge to fit on embedded IoT (end-node) devices, due to their stricter resource constraints (lower area, memory, and energy budgets) as well as their limited computational capabilities. To the best of our knowledge, this is the first endeavor exploring the inherent approximate nature of the LWE problem to undertake a multilevel approximate R-LWE (AxRLWE) architecture with respective security estimates opt for lightweight IoT devices. Undertaking AxRLWE on field-programmable gate arrays (FPGAs), we benchmarked a 64% area reduction cost compared to earlier accurate R-LWE designs at the cost of reduced quantum security. For the application-specific integrated circuits (ASICs) with 45-nm CMOS technology, AxRLWE was benchmarked to fit well within the same area budget of a lightweight ECC processor and consume a third of energy compared to special class of R-Binary LWE (R-BLWE) designs being proposed for an IoT, with a better security level.

Groundwater Storage Analysis Using Deterministic Model Approach for Water Resources Management of Zamfara part of Sokoto-Rima Basin, Nigeria

The study area is entirely located within the Sokoto-Rima hydrological basin of Northwest, Nigeria. Groundwater is widely used for drinking, domestic and agricultural purposes in Zamfara water catchment. The mismanagement of groundwater resources could cause negative effects including depletion of aquifer storage and groundwater level decline. To assure sustainability of the available resources, determination of groundwater budget is necessary. Deterministic model approach was used, which required three quantities (Available water quantity, Abstractible and Storable water volume). In this study meteorological water budget (MWB), water level fluctuation (WTF), and groundwater budget based on geological framework (GBBDF) were used to estimate water budget. Groundwater recharge and abstraction rate were calculated from 280 borehole data across the water catchment area. The average groundwater budget of the study area was calculated as 111,693,470 m3/year with the MWB method and it was calculated as 111,342,057.3m3/year and 73,463,099 m3/year with the WTF and (GBBDF) methods respectively. The groundwater abstraction for domestic/agricultural uses was calculated to be higher to that of aquifer recharge. Thus prudent measure has to be adopted for adequate water use per head as population increase and demographic change will exacerbate more stress on the availability of this precious resources aside the climate change impact. The implication is that further proliferation of borehole wells will deplete the entire aquifer and subject it to be devoid of manageable storage capacity, particularly in the crystalline aquiferous units. It is clear that, if conceptual hydrogeological modelling of the catchment is well known and reliable data are obtained, the MWB method gives accurate results in the basins. However, comparison of multiple methods is valuable for determining the plausible budget amount and for highlighting the uncertainty of the estimate.

Unified Multiple Constant Multipliers for Dynamic Exchange of Low-Precision Kernels on FPGAs

Recent work has shown that small, fast, and power-efficient multiple constant multiplication (MCM) implementations can be realized on FPGAs rather than requiring specialized embedded multipliers. However, the limited silicon area on FPGAs requires applications such as image processing to frequently exchange the multiplier (filter) blocks in a series of filtering operations, and no previous works have considered the MCM problem under topological constraint to avoid time-consuming partial reconfiguration on FPGAs. In this paper, we define a unified MCM (UMCM) problem of finding a unified hardware topology for the multiplier blocks frequently exchanged and introduce a framework termed compatible graph synthesis to solve the problem efficiently. Using a set of parameters to logarithmic shifters, dynamic exchange of multiplier blocks with the unified topology can be realized without partial reconfiguration on FPGAs. Experimental results show that the solution is valuable for applications that require frequent exchange of multiplier blocks on FPGAs due to a limited silicon area budget.

Data assimilation of CrIS NH&amp;lt;sub&amp;gt;3&amp;lt;/sub&amp;gt; satellite observations for improving spatiotemporal NH&amp;lt;sub&amp;gt;3&amp;lt;/sub&amp;gt; distributions in LOTOS-EUROS

Abstract. Atmospheric levels of ammonia (NH3) have substantially increased during the last century, posing a hazard to both human health and environmental quality. The atmospheric budget of NH3, however, is still highly uncertain due to an overall lack of observations. Satellite observations of atmospheric NH3 may help us in the current observational and knowledge gaps. Recent observations of the Cross-track Infrared Sounder (CrIS) provide us with daily, global distributions of NH3. In this study, the CrIS NH3 product is assimilated into the LOTOS-EUROS chemistry transport model using two different methods aimed at improving the modeled spatiotemporal NH3 distributions. In the first method NH3 surface concentrations from CrIS are used to fit spatially varying NH3 emission time factors to redistribute model input NH3 emissions over the year. The second method uses the CrIS NH3 profile to adjust the NH3 emissions using a local ensemble transform Kalman filter (LETKF) in a top-down approach. The two methods are tested separately and combined, focusing on a region in western Europe (Germany, Belgium and the Netherlands). In this region, the mean CrIS NH3 total columns were up to a factor 2 higher than the simulated NH3 columns between 2014 and 2018, which, after assimilating the CrIS NH3 columns using the LETKF algorithm, led to an increase in the total NH3 emissions of up to approximately 30 %. Our results illustrate that CrIS NH3 observations can be used successfully to estimate spatially variable NH3 time factors and improve NH3 emission distributions temporally, especially in spring (March to May). Moreover, the use of the CrIS-based NH3 time factors resulted in an improved comparison with the onset and duration of the NH3 spring peak observed at observation sites at hourly resolution in the Netherlands. Assimilation of the CrIS NH3 columns with the LETKF algorithm is mainly advantageous for improving the spatial concentration distribution of the modeled NH3 fields. Compared to in situ observations, a combination of both methods led to the most significant improvements in modeled monthly NH3 surface concentration and NH4+ wet deposition fields, illustrating the usefulness of the CrIS NH3 products to improve the temporal representativity of the model and better constrain the budget in agricultural areas.

MPU-Sim: A Simulator for In-DRAM Near-Bank Processing Architectures

Despite the promising future of near-bank computing to address the ”memory wall”, there are still critical hardware and software challenges, such as designing compute logics within a stringent area budget and developing software support for efficient data mapping. An open-source simulation framework plays an important role in addressing these challenges, which is unfortunately missing. In this paper, we introduce our open-source simulator for in-DRAM near-bank processing accelerators, MPU-Sim, to complete this missing piece in the research and development of future near-bank processing solutions. We detail the design, implementation, and interface of MPU-Sim, and conduct calibration studies for key hardware components with state-of-the-art simulators to validate our implementations. Finally, we use MPU-Sim for two case studies, DRAM refreshing and thread-block scheduling, to demonstrate the potential usage of MPU-Sim to study hardware and software optimizations for near-bank processing architectures.

A qualitative exploration of the impact of COVID-19 on food decisions of economically disadvantaged families in Northern Ireland

BackgroundThe first UK-wide lockdown to prevent the spread of COVID-19 had a serious financial impact on low-income households, a population already in higher risk of food insecurity and poor dietary choices. Qualitative data on the impact of COVID-19 lockdown on food decisions of UK families are scarce. This study aimed to explore how the measures to control the spread of COVID-19 influenced the food-related decisions of socioeconomically deprived families in Northern Ireland.MethodsA qualitative study captured data from online individual interviews. Participation was open for parents of children 2–17 years old living on a tight budget in urban and rural areas of Northern Ireland. A sampling matrix enabled equal representation of single- and two-parent households, as well as parents of younger children (<12y) and adolescents (≥12y). Data were collected by using the methods of Photovoice and mapping exercise. Data were analysed through a thematic approach.ResultsTwelve online interviews were conducted and five distinct themes were identified reflecting families’ food-related decisions that were affected by the COVID-19 lockdown: 1) food planning; 2) food purchasing; 3) meal preparation; 4) eating and feeding behaviours and 5) eating food prepared outside the house.ConclusionsThe restrictions put in place to inhibit the spread of COVID-19 influenced all aspects of dietary decisions of low-income families. Changes observed during this period included frequent consumption of homemade meals, but also increased unhealthy snacking. Infrequent food shopping encouraged good meal planning, but was also a barrier to securing adequate fresh food. Food-related support including school meal assistance contributed to families’ food security, particularly those of single parents.

Request, Coalesce, Serve, and Forget: Miss-Optimized Memory Systems for Bandwidth-Bound Cache-Unfriendly Applications on FPGAs

Applications such as large-scale sparse linear algebra and graph analytics are challenging to accelerate on FPGAs due to the short irregular memory accesses, resulting in low cache hit rates. Nonblocking caches reduce the bandwidth required by misses by requesting each cache line only once, even when there are multiple misses corresponding to it. However, such reuse mechanism is traditionally implemented using an associative lookup. This limits the number of misses that are considered for reuse to a few tens, at most. In this article, we present an efficient pipeline that can process and store thousands of outstanding misses in cuckoo hash tables in on-chip SRAM with minimal stalls. This brings the same bandwidth advantage as a larger cache for a fraction of the area budget, because outstanding misses do not need a data array, which can significantly speed up irregular memory-bound latency-insensitive applications. In addition, we extend nonblocking caches to generate variable-length bursts to memory, which increases the bandwidth delivered by DRAMs and their controllers. The resulting miss-optimized memory system provides up to 25% speedup with 24× area reduction on 15 large sparse matrix-vector multiplication benchmarks evaluated on an embedded and a datacenter FPGA system.