Dataflow Program Analysis and Refactoring Techniques for Design Space Exploration: MPEG-4 AVC/H.264 Decoder Implementation Case Study

This paper presents a methodology to perform design space exploration of complex signal processing systems implemented using the CAL dataflow language. In the course of space exploration, critical path in dataflow programs is first presented, and then analyzed using a new strategy for computational load reduction. These techniques, together with detecting design bottlenecks, point to the most efficient optimization directions in a complex network. Following these analysis, several new refactoring techniques are introduced and applied on the dataflow program in order to obtain feasible design points in the exploration space. For a MPEG-4 AVC/H.264 decoder software and hardware implementation, the multi-dimensional space can be explored effectively for throughput, resource, and frequency, with real-time decoding range from QCIF to HD resolutions

Design space exploration strategies for FPGA implementation of signal processing systems using CAL dataflow program

This paper presents some strategies for design space exploration of FPGA-based signal processing systems that are specified using the CAL dataflow language. The actor- oriented, high-level of abstraction provided by CAL allows flexible exploration and consequently results in a wide range of feasible design implementations. We have applied and ex- tended the existing techniques for refactoring and pipelining actors and actions by means of critical path analysis, and in- troduced some new buffering techniques based on heuristics. The combinations of these techniques have been applied on the CAL specification of the MPEG-4 video decoder, and synthesized to HDL for evaluation in the design implementa- tion space. Results show that using our configuration for the exploration of 48 design points, a throughput range of roughly 8x has been achieved, for slice, block RAM, frequency, and latency range of 1.3x, 2.5x, 2.5x, and 2.9x respectively

The unfinished agenda of communicable diseases among children and adolescents before the COVID-19 pandemic, 1990-2019: a systematic analysis of the Global Burden of Disease Study 2019

BACKGROUND: Communicable disease control has long been a focus of global health policy. There have been substantial reductions in the burden and mortality of communicable diseases among children younger than 5 years, but we know less about this burden in older children and adolescents, and it is unclear whether current programmes and policies remain aligned with targets for intervention. This knowledge is especially important for policy and programmes in the context of the COVID-19 pandemic. We aimed to use the Global Burden of Disease (GBD) Study 2019 to systematically characterise the burden of communicable diseases across childhood and adolescence. METHODS: In this systematic analysis of the GBD study from 1990 to 2019, all communicable diseases and their manifestations as modelled within GBD 2019 were included, categorised as 16 subgroups of common diseases or presentations. Data were reported for absolute count, prevalence, and incidence across measures of cause-specific mortality (deaths and years of life lost), disability (years lived with disability [YLDs]), and disease burden (disability-adjusted life-years [DALYs]) for children and adolescents aged 0-24 years. Data were reported across the Socio-demographic Index (SDI) and across time (1990-2019), and for 204 countries and territories. For HIV, we reported the mortality-to-incidence ratio (MIR) as a measure of health system performance. FINDINGS: In 2019, there were 3·0 million deaths and 30·0 million years of healthy life lost to disability (as measured by YLDs), corresponding to 288·4 million DALYs from communicable diseases among children and adolescents globally (57·3% of total communicable disease burden across all ages). Over time, there has been a shift in communicable disease burden from young children to older children and adolescents (largely driven by the considerable reductions in children younger than 5 years and slower progress elsewhere), although children younger than 5 years still accounted for most of the communicable disease burden in 2019. Disease burden and mortality were predominantly in low-SDI settings, with high and high-middle SDI settings also having an appreciable burden of communicable disease morbidity (4·0 million YLDs in 2019 alone). Three cause groups (enteric infections, lower-respiratory-tract infections, and malaria) accounted for 59·8% of the global communicable disease burden in children and adolescents, with tuberculosis and HIV both emerging as important causes during adolescence. HIV was the only cause for which disease burden increased over time, particularly in children and adolescents older than 5 years, and especially in females. Excess MIRs for HIV were observed for males aged 15-19 years in low-SDI settings. INTERPRETATION: Our analysis supports continued policy focus on enteric infections and lower-respiratory-tract infections, with orientation to children younger than 5 years in settings of low socioeconomic development. However, efforts should also be targeted to other conditions, particularly HIV, given its increased burden in older children and adolescents. Older children and adolescents also experience a large burden of communicable disease, further highlighting the need for efforts to extend beyond the first 5 years of life. Our analysis also identified substantial morbidity caused by communicable diseases affecting child and adolescent health across the world. FUNDING: The Australian National Health and Medical Research Council Centre for Research Excellence for Driving Investment in Global Adolescent Health and the Bill & Melinda Gates Foundation

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Optimization Methodologies for Complex FPGA-based Signal Processing Systems with CAL

Signal processing designs are becoming increasingly complex with demands for more advanced algorithms. Designers are now seeking high-level tools and methodology to help manage complexity and increase productivity. Recently, CAL dataflow language has been specified which is capable of synthesizing dataflow description into RTL codes for hardware implementation, and based on several case studies, have shown promising results. However, no work has been done on global network analysis, which could increase the optimization space. In this paper, we introduce methodologies to analyze and optimize CAL programs by determining which actions should be parallelized, pipelined, or refactored for the highest throughput gain, and then providing tools and techniques to achieve this using minimum resource. As a case study on the RVC MPEG-4 SP Intra decoder for implementation on Virtex-5 FPGA, experimental results confirmed our analysis with throughput gain of up to 3.5x using relatively-minor additional slice compared to the reference design

Methodology and Technique to Improve Throughput of FPGA-based CAL Dataflow Programs: Case Study of the RVC MPEG-4 SP Intra Decoder

The specification of complex signal processing systems in hardware by means of HDL is no longer the appropriate way since they are known to be time consuming to design, and less flexible to extend features. Recently, \CAL dataflow language was specified to increase productivity and scalability, with ability to synthesize to HDL for hardware implementation. In this paper, a new methodology to improve throughput of dataflow-based hardware designs is given by analyzing \CAL programs using the profiling tool. As a case study, we analyzed the RVC MPEG-4 SP Intra decoder and found that the texture decoding part has the highest improvement factor. We have also introduced the luminance texture splitting technique as the improvement method by increasing the level of parallelism in the decoder. Experimental results of implementation on Virtex-5 FPGA confirmed our analysis with throughput in- crease of up to 50.5\% with only 4.3\% additional slice

Trust model for reliable grouping-based communications in vehicular ad-hoc networks

This paper presents a high-reliability Grouping-Based communications trust model in Vehicular Ad-hoc Networks (VANET). The proposed solution consists of two distinct components: First, the Dynamic Group Head Selection (DGHS) scheme to improve the Group Head’s (GH) stability by considering the reliability of the communication link with the Road Side Unit (RSU). Second, a hybrid Dynamic Trust Model (DTM) scheme improves trustworthiness by considering the node’s dynamic conditions and records. Average GH Lifetime and Average Query Success Rate were used as metrics to evaluate the performance of the grouping algorithms to those of Cluster-Based Location Service (CBLS) and Trust-based Security for Message Exchange (TSME). The proposed DTM was compared to TSME and MiTM Attack Resistant Trust Model (MARINE). With a maximum density of 900 vehicles, DTM improves the average GH lifetime by 43% compared to CBLS and 19% compared to TSME. Similarly, DTM increases the query success rate by 10% compared to the CBLS and 23% compared to the TSME, even at the slowest speed (40 km/h). In terms of node density precision, DTM decreases by around 5% for MARINE and 10% for the TSME approach. In conclusion, it has been shown that the proposed schemes are reliable for various position-based VANET applications that need precise positioning and trusted messaging