Probabilistic Compute-in-Memory Design For Efficient Markov Chain Monte Carlo Sampling

Markov chain Monte Carlo (MCMC) is a widely used sampling method in modern artificial intelligence and probabilistic computing systems. It involves repetitive random number generations and thus often dominates the latency of probabilistic model computing. Hence, we propose a compute-in-memory (CIM) based MCMC design as a hardware acceleration solution. This work investigates SRAM bitcell stochasticity and proposes a novel ``pseudo-read'' operation, based on which we offer a block-wise random number generation circuit scheme for fast random number generation. Moreover, this work proposes a novel multi-stage exclusive-OR gate (MSXOR) design method to generate strictly uniformly distributed random numbers. The probability error deviating from a uniform distribution is suppressed under $10^{-5}$. Also, this work presents a novel in-memory copy circuit scheme to realize data copy inside a CIM sub-array, significantly reducing the use of R/W circuits for power saving. Evaluated in a commercial 28-nm process development kit, this CIM-based MCMC design generates 4-bit$\sim$32-bit samples with an energy efficiency of $0.53$~pJ/sample and high throughput of up to $166.7$M~samples/s. Compared to conventional processors, the overall energy efficiency improves $5.41\times10^{11}$ to $2.33\times10^{12}$ times

DDC-PIM: Efficient Algorithm/Architecture Co-design for Doubling Data Capacity of SRAM-based Processing-In-Memory

Processing-in-memory (PIM), as a novel computing paradigm, provides significant performance benefits from the aspect of effective data movement reduction. SRAM-based PIM has been demonstrated as one of the most promising candidates due to its endurance and compatibility. However, the integration density of SRAM-based PIM is much lower than other non-volatile memory-based ones, due to its inherent 6T structure for storing a single bit. Within comparable area constraints, SRAM-based PIM exhibits notably lower capacity. Thus, aiming to unleash its capacity potential, we propose DDC-PIM, an efficient algorithm/architecture co-design methodology that effectively doubles the equivalent data capacity. At the algorithmic level, we propose a filter-wise complementary correlation (FCC) algorithm to obtain a bitwise complementary pair. At the architecture level, we exploit the intrinsic cross-coupled structure of 6T SRAM to store the bitwise complementary pair in their complementary states ($Q/\overline{Q}$), thereby maximizing the data capacity of each SRAM cell. The dual-broadcast input structure and reconfigurable unit support both depthwise and pointwise convolution, adhering to the requirements of various neural networks. Evaluation results show that DDC-PIM yields about $2.84\times$ speedup on MobileNetV2 and $2.69\times$ on EfficientNet-B0 with negligible accuracy loss compared with PIM baseline implementation. Compared with state-of-the-art SRAM-based PIM macros, DDC-PIM achieves up to $8.41\times$ and $2.75\times$ improvement in weight density and area efficiency, respectively.Comment: 14 pages, to be published in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD

Climate benefits of intact Amazon forests and the biophysical consequences of disturbance

Tropical forests have an important regulating influence on local and regional climate, through modulating the exchange of moisture and energy between the land and the atmosphere. Deforestation disrupts this exchange, though the climatic consequences of progressive, patch-scale deforestation of formerly intact forested landscapes have not previously been assessed. Remote sensing datasets of land surface and atmospheric variables were used to compare the climate responses of Amazon evergreen broadleaf forests that lost their intact status between 2000 and 2013. Clear gradients in environmental change with increasing disturbance were observed. Leaf area index (LAI) showed progressively stronger reductions as forest loss increased, with evapotranspiration (ET) showing a comparative decline. These changes in LAI and ET were related to changes in temperature (T), with increased warming as deforestation increased. Severe deforestation of intact Amazon forest, defined as areas where canopy cover was reduced below 70 %, was shown to have increased daytime land surface T by 0.44 °C over the study period. Differences between intact and disturbed forests were most pronounced during the dry season, with severely deforested areas warming as much as 1.5 °C. Maintenance of canopy cover was identified as an important factor in minimising the impacts of disturbance. Overall, the results highlight the climate benefits provided by intact tropical forests, providing further evidence that protecting intact forests is of utmost importance

Tree Cover Mapping Based on Sentinel-2 Images Demonstrate High Thematic Accuracy in Europe

The spatial and temporal distribution of trees has a large impact on human health and the environment through contributions to important climate mechanisms as well as commercial, recreational and social activities in society. A range of tree mapping methodologies has been presented in the literature, but tree cover estimates still differ widely between the individual datasets, and comparisons of the thematic accuracy of the resulting tree maps are rather scarce. The Copernicus Sentinel-2 satellites, which were launched in 2015 and 2017, have a combination of high spatial and temporal resolution. Given that this is a new satellite, a substantial amount of research on development of tree mapping algorithms as well as accuracy assessment of said algorithms have to be done in the years to come. To contribute to this process, a tree map produced through unsupervised classification was created for six Sentinel-2 tiles. The agreement between the tree map and the corresponding national forest inventory, as a function of the band combination chosen, was analysed and the thematic accuracy was assessed for two out of the six tiles. The results show that the highest agreement between the present tree map and the national forest inventory was found for bands 2, 3, 6 and 12. The present tree map has a relative difference in tree cover between 8% and 79% compared to previous estimates, but results are characterised by large scatter. Lastly, it is shown that the overall thematic accuracy of the present map is up to 90%, with the user’s accuracy ranging from 34.85 % to 92.10 %, and the producer’s accuracy ranging from 23.80 % to 97.60 % for the various thematic classes. This demonstrates that tree maps with high thematic accuracy can be produced from Sentinel-2. In the future the thematic accuracy can be increased even more through the use of temporal averaging in the mapping procedure, which will enable an accurate estimate of the European tree cover

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

High-Sensitivity Optical Fiber-Based Glucose Sensor Using Helical Intermediate-Period Fiber Grating

An all-fiber glucose sensor is proposed and demonstrated based on a helical intermediate-period fiber grating (HIPFG) produced by using a hydrogen/oxygen flame heating method. The HIPFG, with a grating length of 1.7 cm and a period of 35 μm, presents four sets of double dips with low insertion losses and strong coupling strengths in the transmission spectrum. The HIPFG possesses an averaged refractive index (RI) sensitivity of 213.6 nm/RIU nm/RIU in the RI range of 1.33–1.36 and a highest RI sensitivity of 472 nm/RIU at RI of 1.395. In addition, the HIPFG is demonstrated with a low-temperature sensitivity of 3.67 pm/°C, which promises a self-temperature compensation in glucose detection. In the glucose-sensing test, the HIPFG sensor manifests a detection sensitivity of 0.026 nm/(mg/mL) and a limit of detection (LOD) of 1 mg/mL. Moreover, the HIPFG sensor exhibits good stability in 2 h, indicating its capacity for long-time detection. The properties of easy fabrication, high flexibility, insensitivity to temperature, and good stability of the proposed HIPFG endow it with a promising potential for long-term and compact biosensors

Epidemiological clustered characteristics of coronavirus disease 2019 (COVID-19) in three phases of transmission in Jilin Province, China

The current epidemiological status of the new coronary pneumonia epidemic in China is being explored to prevent and control the localized dissemination of aggregated outbreaks. This study analyzed the characteristics of new outbreaks of coronavirus disease 2019 (COVID-19) at three stages of aggregated outbreaks in Jilin Province, China, to provide a reference for the prevention and control of aggregated outbreaks. Case information were collected from all patients in Jilin Province from January 12, 2020 to the present. The epidemic was divided into three stages according to the time of onset. The first stage comprised 97 cases reported from January 12, 2020 to February 19, 2020, during which 17 aggregated outbreaks occurred. The second comprised 43 cases reported from April 25, 2020 and May 23, 2020, involving one aggregated outbreak. The third comprised 435 cases reported on January 10, 2021 and February 9, 2021, involving one aggregated outbreak. The relationship between aggregated and non-aggregated cases in the first phase of the outbreak and the difference between imported and local cases during the aggregated outbreak were assess using statistical analysis, and the differences in the baseline information between the three phases were analyzed. The incubation periods of the three phases were 10 days, 8 days, and 5 days. The number of aggregated epidemic events in Jilin Province tended to increase and then decrease over time. The clustered events in Jilin Province were divided into four categories: household contact (14 times, 51 cases); household contact and public places (one time, three cases); household contact, public places, and gatherings (one time, six cases); and household contact, public places, gatherings, and work (three times, 495 cases). Clustered events occurred mainly between January 22, 2020, and February 4, 2020. Among all cases in the first phase of the outbreak, the method of detection and the time from diagnosis to discharge were longer in aggregated cases than in non-aggregated cases, and that the source of infection and renewal cases were more frequent and more likely to be detected in the outpatient clinics during aggregated outbreaks than the imported cases. The second phase of the epidemic showed significant spatial variability (Moran’s I<0, P<0.05). The third stage of the epidemic occurred in a higher proportion of individuals aged 50–90 years and within a shorter incubation period compared with the first two stages. The current focus of prevention and control of the COVID-19 epidemic in Jilin Province is to strictly implement the restrictions on gatherings and to perform timely screening and isolation of close contacts of infectious sources while strengthening the supervision of the inflow of people from outside the region. Simultaneously, more targeted prevention and control measures can be implemented for different age groups and occupations