From Functional Programs to Pipelined Dataflow Circuits

We present a translation from programs expressed in a functional IR into dataflow networks as an intermediate step within a Haskell-to-Hardware compiler. Our networks exploit pipeline parallelism, particularly across multiple tail-recursive calls, via non-strict function evaluation. To handle the long-latency memory operations common to our target applications, we employ a latency-insensitive methodology that ensures arbitrary delays do not change the functionality of the circuit. We present empirical results comparing our networks against their strict counterparts, showing that nonstrictness can mitigate small increases in memory latency and improve overall performance by up to 2x

Hardware in Haskell: Implementing Memories in a Stream-Based World

Recursive functions and data types pose significant challenges for a Haskell-to-hardware compiler. Directly translating these structures yields infinitely large circuits; a subtler approach is required. We propose a sequence of abstraction-lowering transformations that exposes time and memory in a Haskell program, producing a simpler form for hardware translation. This paper outlines these transformations on a specific example; future research will focus on generalizing and automating them in our group's compiler

Simulations Inform Design of Regional Occupancy-Based Monitoring for a Sparsely Distributed, Territorial Species

Sparsely distributed species attract management concern. Insufficient information on population trends, however, challenges conservation and funding prioritization. Occupancybased methods are cost effective and therefore attractive for broad-scale trend monitoring, but appropriate sampling design and inference depend on particulars of the study system. We employed spatially explicit simulations to inform regional occupancy-based monitoring of white-headed woodpeckers (Picoides albolvartus), a sparsely distributed, territorial species threatened by habitat decline and degradation. We incorporated basic knowledge of species ecology into population simulations to compare statistical power and trend estimation error under alternative scenarios. Sampling effort needed to achieve adequate power to observe a long-term population trend (? 80% chance to observe a 2% yearly decline over 20 years) consisted of annually monitoring ? 120 transects using the single-survey approach or ? 90 transects using a repeat-survey approach. The single-survey approach, which employs occupancy as an index of abundance and requires auxiliary information to account for detectability, provided more power for a given level of sampling effort than repeat-survey approaches. Alternate allocation schemes improved statistical power and trend estimates over the baseline (surveying 10 points within all transects annually), including surveying a subset (33%) of transects each year (i.e., a panel design) and surveying fewer points per transect in exchange for a larger spatial sample. Considering this case study, single-survey methods (with separate evaluation of detectability), panel designs, and aligning sampling resolution with home range size could likely benefit broad-scale occupancy-based monitoring of other sparsely distributed and mobile species

State Behavioral Scale (SBS) A Sedation Assessment Instrument for Infants and Young Children Supported on Mechanical Ventilation

Objective: To develop and test the reliability and validity of the State Behavioral Scale for use in describing sedation/agitation levels in young intubated patients supported on mechanical ventilation. Design: In this prospective, psychometric evaluation, pairs of trained pediatric critical care nurse evaluators simultaneously and independently assessed a convenience sample of pediatric intensive care unit patients along eight state/behavioral dimensions and a numeric rating scale (NRS) of 0 (extremely sedated) to 10 (extremely agitated). The eight dimensions were derived from the sedation/agitation literature and expert opinion and included respiratory drive, response to ventilation, coughing, best response to stimulation, attentiveness to careprovider, tolerance to care, consolability, and movement after consoled, each with 3–5 levels. Setting: An 18-bed pediatric medical–surgical intensive care unit and 26-bed pediatric cardiovascular intensive care unit in a university-affiliated academic children’s hospital. Patients: A total of 91 intubated mechanically ventilated patients 6 wks to 6 yrs of age provided a median of two observations (interquartile range, 1–3) for a total of 198 sets of observations. Excluded were postoperative patients or those receiving neuromuscular blockade. Interventions: Patients were observed for 1 min, and then incremental levels of stimulation were applied until patient response. After 2 mins of consoling, the state behavioral assessment and NRS were completed. Measurements: Weighted kappa and intraclass coefficients were generated to assess interrater reliability of the eight dimension and NRS ratings. Distinct state behavior profiles were empirically identified from the dimension ratings using hierarchical cluster analysis using a squared Euclidean distance measure and between-groups linkage. Construct validity of these profiles was assessed by comparing group mean NRS scores using one-way analysis of variance. Main Results: Weighted kappa scores for all 198 dimension ratings ranged from .44 to .76, indicating moderate to good interrater reliability. The intraclass coefficient of .79 was high for NRS ratings. Cluster analysis revealed five distinct state profiles, with mean NRS ratings of 1.1, 2.5, 4.0, 5.3, and 7.6, all of which differed significantly from each other (F = 75.8, p \u3c .001), supporting the profiles’ construct validity. Conclusions: Based on empirically derived state behavior profiles, we have constructed the State Behavioral Scale to allow systematic description of the sedation–agitation continuum in young pediatric patients supported on mechanical ventilation. Further studies including prospective validation and describing the effect of State Behavioral Scale implementation on clinical outcomes, including the quality of sedation and length of mechanical ventilation, are warranted

Hardware Synthesis from a Recursive Functional Language

Abstraction in hardware description languages stalled at the register-transfer level decades ago, yet few alternatives have had much success, in part because they provide only modest gains in expressivity. We propose to make a much larger jump: a compiler that synthesizes hardware from behavioral functional specifications. Our compiler translates general Haskell programs into a restricted intermediate representation before applying a series of semantics-preserving transformations, concluding with a simple syntax-directed translation to SystemVerilog. Here, we present the overall framework for this compiler, focusing on the IRs involved and our method for translating general recursive functions into equivalent hardware. We conclude with experimental results that depict the performance and resource usage of the circuitry generated with our compiler

Compositional Dataflow Circuits

We present a technique for implementing dataflow networks as compositional hardware circuits. We first define an abstract dataflow model with unbounded buffers that supports data-dependent blocks (mux, demux, and nondeterministic merge); we then show how to faithfully implement such networks with bounded buffers and handshaking. Handshaking admits compositionality: our circuits can be connected with or without buffers, and combinational cycles arise only from a completely unbuffered cycle. While bounding buffer sizes can cause the system to deadlock prematurely, the system is guaranteed to produce the same, correct, data before then. Thus, unless the system deadlocks, inserting or removing buffers only affects its performance. We demonstrate how this enables design space to be explored

The Withdrawal Assessment Tool–1 (WAT–1): An Assessment Instrument for Monitoring Opioid and Benzodiazepine Withdrawal Symptoms in Pediatric Patients

Objective: To develop and test the validity and reliability of the Withdrawal Assessment Tool–1 for monitoring opioid and benzodiazepine withdrawal symptoms in pediatric patients. Design: Prospective psychometric evaluation. Pediatric critical care nurses assessed eligible at-risk pediatric patients for the presence of 19 withdrawal symptoms and rated the patient’s overall withdrawal intensity using a Numeric Rating Scale where zero indicated no withdrawal and 10 indicated worst possible withdrawal. The 19 symptoms were derived from the Opioid and Benzodiazepine Withdrawal Score, the literature and expert opinion. Setting: Two pediatric intensive care units in university-affiliated academic children’s hospitals. Patients: Eighty-three pediatric patients, median age 35 mos (interquartile range: 7 mos−10 yrs), recovering from acute respiratory failure who were being weaned from more than 5 days of continuous infusion or round-the-clock opioid and benzodiazepine administration. Interventions: Repeated observations during analgesia and sedative weaning. A total of 1040 withdrawal symptom assessments were completed, with a median (interquartile range) of 11 (6–16) per patient over 6.6 (4.8−11) days. Measurements and Main Results: Generalized linear modeling was used to analyze each symptom in relation to withdrawal intensity ratings, adjusted for site, subject, and age group. Symptoms with high redundancy or low levels of association with withdrawal intensity ratings were dropped, resulting in an 11-item (12-point) scale. Concurrent validity was indicated by high sensitivity (0.872) and specificity (0.880) for Withdrawal Assessment Tool–1 \u3e 3 predicting Numeric Rating Scale \u3e 4. Construct validity was supported by significant differences in drug exposure, length of treatment and weaning from sedation, length of mechanical ventilation and intensive care unit stay for patients with Withdrawal Assessment Tool–1 scores \u3e 3 compared with those with lower scores. Conclusions: The Withdrawal Assessment Tool–1 shows excellent preliminary psychometric performance when used to assess clinically important withdrawal symptoms in the pediatric intensive care unit setting. Further psychometric evaluation in diverse at-risk groups is needed

Cache Impacts of Datatype Acceleration

Hardware acceleration is a widely accepted solution for performance and energy efficient computation because it removes unnecessary hardware for general computation while delivering exceptional performance via specialized control paths and execution units. The spectrum of accelerators available today ranges from coarse-grain off-load engines such as GPUs to fine-grain instruction set extensions such as SSE. This research explores the benefits and challenges of managing memory at the data-structure level and exposing those operations directly to the ISA. We call these instructions. Abstract Datatype Instructions (ADIs). This paper quantifies the performance and energy impact of ADIs on the instruction and data cache hierarchies. For instruction fetch, our measurements indicate that ADIs can result in 21-48% and 16-27% reductions in instruction fetch time and energy respectively. For data delivery, we observe a 22-40% reduction in total data read/write time and 9-30% in total data read/write energy

Trial-unique, delayed nonmatching-to-location (TUNL) touchscreen testing for mice: sensitivity to dorsal hippocampal dysfunction.

RATIONALE: The hippocampus is implicated in many of the cognitive impairments observed in conditions such as Alzheimer's disease (AD) and schizophrenia (SCZ). Often, mice are the species of choice for models of these diseases and the study of the relationship between brain and behaviour more generally. Thus, automated and efficient hippocampal-sensitive cognitive tests for the mouse are important for developing therapeutic targets for these diseases, and understanding brain-behaviour relationships. One promising option is to adapt the touchscreen-based trial-unique nonmatching-to-location (TUNL) task that has been shown to be sensitive to hippocampal dysfunction in the rat. OBJECTIVES: This study aims to adapt the TUNL task for use in mice and to test for hippocampus-dependency of the task. METHODS: TUNL training protocols were altered such that C57BL/6 mice were able to acquire the task. Following acquisition, dysfunction of the dorsal hippocampus (dHp) was induced using a fibre-sparing excitotoxin, and the effects of manipulation of several task parameters were examined. RESULTS: Mice could acquire the TUNL task using training optimised for the mouse (experiments 1). TUNL was found to be sensitive to dHp dysfunction in the mouse (experiments 2, 3 and 4). In addition, we observed that performance of dHp dysfunction group was somewhat consistently lower when sample locations were presented in the centre of the screen. CONCLUSIONS: This study opens up the possibility of testing both mouse and rat models on this flexible and hippocampus-sensitive touchscreen task.CHK received funding from the Korean Health Technology R&D Project, Ministry of Health & Welfare, Republic of Korea (HI11C1183). CJH, LMS and TJB were funded by Medical Research Council/Wellcome Trust grant 089703/Z/09/Z. CR, LMS and TJB were funded by Alzheimer’s Research UK [ART/ESG2010/1]. ACM, MHE, CAO, LMS and TJB also received funding from the Innovative Medicine Initiative Joint Undertaking under grant agreement no 115008 of which resources are composed of EFPIA in-kind contribution and financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013).This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s00213-015-4017-