LogicWiSARD: Memoryless synthesis of weightless neural networks

Weightless neural networks (WNNs) are an alternative pattern recognition technique where RAM nodes function as neurons. As both training and inference require mostly table lookups, few additions, and no multiplications, WNNs are suitable for high-performance and low-power embedded applications. This work introduces a novel approach to implement WiSARD, the leading WNN state-of-the-art architecture, completely eliminating memories and arithmetic circuits and utilizing only logic functions. The approach creates compressed minimized implementations by converting trained WNN nodes from lookup tables to logic functions. The proposed LogicWiSARD is implemented in FPGA and ASIC technologies to illustrate its suitability for edge inference. Experimental results show more than 80% reduction in energy consumption when the proposed LogicWiSARD model is compared with a multilayer perceptron network (MLP) of equivalent accuracy. Compared to previous work on FPGA implementations for WNNs, convolutional neural networks, and binary neural networks, the energy savings of LogicWiSARD range between 32.2% and 99.6%.info:eu-repo/semantics/acceptedVersio

ULEEN: A Novel Architecture for Ultra Low-Energy Edge Neural Networks

The deployment of AI models on low-power, real-time edge devices requires accelerators for which energy, latency, and area are all first-order concerns. There are many approaches to enabling deep neural networks (DNNs) in this domain, including pruning, quantization, compression, and binary neural networks (BNNs), but with the emergence of the "extreme edge", there is now a demand for even more efficient models. In order to meet the constraints of ultra-low-energy devices, we propose ULEEN, a model architecture based on weightless neural networks. Weightless neural networks (WNNs) are a class of neural model which use table lookups, not arithmetic, to perform computation. The elimination of energy-intensive arithmetic operations makes WNNs theoretically well suited for edge inference; however, they have historically suffered from poor accuracy and excessive memory usage. ULEEN incorporates algorithmic improvements and a novel training strategy inspired by BNNs to make significant strides in improving accuracy and reducing model size. We compare FPGA and ASIC implementations of an inference accelerator for ULEEN against edge-optimized DNN and BNN devices. On a Xilinx Zynq Z-7045 FPGA, we demonstrate classification on the MNIST dataset at 14.3 million inferences per second (13 million inferences/Joule) with 0.21 $\mu$s latency and 96.2% accuracy, while Xilinx FINN achieves 12.3 million inferences per second (1.69 million inferences/Joule) with 0.31 $\mu$s latency and 95.83% accuracy. In a 45nm ASIC, we achieve 5.1 million inferences/Joule and 38.5 million inferences/second at 98.46% accuracy, while a quantized Bit Fusion model achieves 9230 inferences/Joule and 19,100 inferences/second at 99.35% accuracy. In our search for ever more efficient edge devices, ULEEN shows that WNNs are deserving of consideration.Comment: 14 pages, 14 figures Portions of this article draw heavily from arXiv:2203.01479, most notably sections 5E and 5F.

A Randomized Trial of the Optimum Duration of Acoustic Pulse Thrombolysis Procedure in Acute Intermediate-Risk Pulmonary Embolism: The OPTALYSE PE Trial.

The aim of this study was to determine the lowest optimal tissue plasminogen activator (tPA) dose and delivery duration using ultrasound-facilitated catheter-directed thrombolysis (USCDT) for the treatment of acute intermediate-risk (submassive) pulmonary embolism.This article is freely available via Open Access. Click on the Additional Link above to access the full-text via the publisher's site

Description and performance of track and primary-vertex reconstruction with the CMS tracker

A description is provided of the software algorithms developed for the CMS tracker both for reconstructing charged-particle trajectories in proton-proton interactions and for using the resulting tracks to estimate the positions of the LHC luminous region and individual primary-interaction vertices. Despite the very hostile environment at the LHC, the performance obtained with these algorithms is found to be excellent. For tbar t events under typical 2011 pileup conditions, the average track-reconstruction efficiency for promptly-produced charged particles with transverse momenta of pT > 0.9GeV is 94% for pseudorapidities of |η| < 0.9 and 85% for 0.9 < |η| < 2.5. The inefficiency is caused mainly by hadrons that undergo nuclear interactions in the tracker material. For isolated muons, the corresponding efficiencies are essentially 100%. For isolated muons of pT = 100GeV emitted at |η| < 1.4, the resolutions are approximately 2.8% in pT, and respectively, 10μm and 30μm in the transverse and longitudinal impact parameters. The position resolution achieved for reconstructed primary vertices that correspond to interesting pp collisions is 10–12μm in each of the three spatial dimensions. The tracking and vertexing software is fast and flexible, and easily adaptable to other functions, such as fast tracking for the trigger, or dedicated tracking for electrons that takes into account bremsstrahlung

Alignment of the CMS tracker with LHC and cosmic ray data

© CERN 2014 for the benefit of the CMS collaboration, published under the terms of the Creative Commons Attribution 3.0 License by IOP Publishing Ltd and Sissa Medialab srl. Any further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation and DOI.The central component of the CMS detector is the largest silicon tracker ever built. The precise alignment of this complex device is a formidable challenge, and only achievable with a significant extension of the technologies routinely used for tracking detectors in the past. This article describes the full-scale alignment procedure as it is used during LHC operations. Among the specific features of the method are the simultaneous determination of up to 200 000 alignment parameters with tracks, the measurement of individual sensor curvature parameters, the control of systematic misalignment effects, and the implementation of the whole procedure in a multi-processor environment for high execution speed. Overall, the achieved statistical accuracy on the module alignment is found to be significantly better than 10μm

Usage patterns and 2-year outcomes with the TAXUS express stent: results of the US ARRIVE 1 registry.

BACKGROUND: It is unclear how well the long-term safety and effectiveness of drug-eluting stents observed in tightly defined randomized controlled trials (RCT) translates to expanded use in routine practice. METHODS: The FDA-mandated TAXUS Express(2) ARRIVE 1 postmarket registry was designed to consecutively enroll patients receiving \u3e or = 1 TAXUS stent in low-, medium-, and high-volume US sites (n = 50). All cardiac events plus an additional 20% sample of records were monitored and all endpoints were independently adjudicated. RESULTS: Detailed follow-up data through 2 years were compiled for 2,487 patients (95%). Simple-use (on-label) ARRIVE 1 patients (35%) had outcomes similar to 4 pooled TAXUS RCTs for death (3.5% vs. 3.4%, respectively, P = 0.78), Q-wave myocardial infarction (QWMI, 0.7% vs. 0.9%, P = 0.72), and stent thrombosis (ST, 2.2% vs. 1.2%, P = 0.12), but lower target vessel revascularization (7.8% vs. 13.4%, P \u3c 0.0001). Compared with simple-use, cases representing expanded use to treat broader patient/lesion characteristics showed higher 2-year rates for death (7.4% vs. 3.5%, respectively, P = 0.0003), target lesion revascularization (9.4% vs. 5.8%, P = 0.0031), and ST (3.4% vs. 2.2%, P = 0.061, concentrated early in the first year). CONCLUSIONS: By including methods usually found in RCT, ARRIVE 1 captured a broad spectrum of disease treated in standard practice with high levels of ascertainment of clinical outcomes. In the more complicated cases, expectedly higher adverse event rates were seen compared to that found in the simple-use cases or pivotal RCT. These results have now been included in the Directions for Use, to aid in physician and patient decision-making

Platelet microparticles and calcium homeostasis in acute coronary ischemias

Elevation of free cytoplasmic calcium is the common pathway of platelet activation, leading to shape change, shedding of platelet microparticles (PMP), aggregation, and secretion of internal granules, including expression of CD62p on the surface. Platelet activation is well documented in unstable angina (UA) and acute myocardial infarction (MI). We investigated the following markers of platelet activation in 55 patients undergoing coronary angiography for suspected CAD: free cytoplasmic calcium, [Ca2+]cyt, PMP, CD62p expression, and platelet/leukocyte (P/L) interaction. [CA2+]cyt was measured by Fluo‐3 and the other measurements were by flow cytometry. Patients were classified into three groups: unstable angina (UA, n = 11), recent myocardial infarction (MI, n = 11), and patient controls (CTL, n = 33). Blood was drawn before infusion of heparin through femoral lines at the time of catheterization for assays. Results: (1) PMP values were significantly higher in both UA and MI than in CTL, P < 0.05. There was no difference between UA and MI. (2) P/L interaction was significantly elevated only in UA, P < 0.05. (3) CD62p expression on free platelets did not differ significantly between any of the three groups. (4) The resting [Ca2+]cyt, thrombin‐induced CA2+ influx, and release of CA2+ from internal stores were all significantly higher in platelets from the combined patient group (UA + MI) than in the patient group, P < 0.001 Conclusions: Results on calcium hemostasis and PMP were significantly different in patients with acute coronary syndromes than those with stable angina or no coronay ischemia; this may reflect underlying pathophysiology of acute coronary ischemia. P/L interaction was higher only in the UA group, suggesting a role of leukocytes in the UA. Am. J. Hematol. 54:95–101, 1997 © 1997 Wiley‐Liss, Inc