Quality of Service Driven Runtime Resource Allocation in Reconfigurable HPC Architectures

Heterogeneous System Architectures (HSA) are gaining importance in the High Performance Computing (HPC) domain due to increasing computational requirements coupled with energy consumption concerns, which conventional CPU architectures fail to effectively address. Systems based on Field Programmable Gate Array (FPGA) recently emerged as an effective alternative to Graphical Processing Units (GPUs) for demanding HPC applications, although they lack the abstractions available in conventional CPU-based systems. This work tackles the problem of runtime resource management of a system using FPGA-based co-processors to accelerate multi-programmed HPC workloads. We propose a novel resource manager able to dynamically vary the number of FPGAs allocated to each of the jobs running in a multi-accelerator system, with the goal of meeting a given Quality of Service metric for the running jobs measured in terms of deadline or throughput. We implement the proposed resource manager in a commercial HPC system, evaluating its behavior with representative workloads

Photophobia and migraine outcome during treatment with galcanezumab

BackgroundCalcitonin gene-related peptide (CGRP) plays a pivotal role in migraine physiology, not only regarding migraine pain but also associated symptoms such as photophobia. The aim of the present study was to assess monoclonal antibodies targeting CGRP efficacy not only in terms of headache and migraine frequency and disability but also in reducing ictal photophobia.Material and methodsThis is a retrospective observational study, conducted at the Headache Center–ASST Spedali Civili Brescia. All patients in monthly treatment with galcanezumab with at least a 6-month follow-up in September 2022 with reported severe photophobia during migraine attacks were included. Data regarding headache frequency, analgesics consumption, and migraine disability were collected quarterly. Moreover, patients were asked the following information regarding photophobia: (1) whether they noticed an improvement in photophobia during migraine attacks since galcanezumab introduction; (2) the degree of photophobia improvement (low, moderate, and high); and (3) timing photophobia improvement.ResultsForty-seven patients were enrolled in the present study as they met the inclusion criteria. Seventeen patients had a diagnosis of high-frequency episodic migraine and 30 of chronic migraine. From baseline to T3 and T6, a significant improvement in terms of headache days (19.2 ± 7.6 vs. 8.6 ± 6.8 vs. 7.7 ± 5.7; p < 0.0001), migraine days (10.4 ± 6.7 vs. 2.9 ± 4.3 vs. 3.6 ± 2.8; p < 0.0001), analgesics consumption (25.1 ± 28.2 vs. 7.6 ± 7.5 vs. 7.6 ± 8.1; p < 0.0001), MIDAS score (82.1 ± 48.4 vs. 21.6 ± 17.6 vs. 18.1 ± 20.5; p < 0.0001), and HIT-6 score (66.2 ± 6.2 vs. 57.2 ± 8.6 vs. 56.6 ± 7.6; p < 0.0001) was found. Thirty-two patients (68.1%) reported a significant improvement in ictal photophobia, with over half of the patients reporting it within the first month of treatment. Photophobia improvement was more frequent in patients with episodic migraine (p = 0.02) and triptans responders (p = 0.03).ConclusionsThe present study confirms previous reports regarding galcanezumab efficacy beyond migraine frequency. In particular, over 60% of patients, in our cohort, documented a significant improvement also in reducing ictal photophobia. This improvement was, in most patients, moderate to high, and within the first 6 months of treatment, regardless of the clinical response on migraine frequency

The annotation and the usage of scientific databases could be improved with public issue tracker software

Since the publication of their longtime predecessor The Atlas of Protein Sequences and Structures in 1965 by Margaret Dayhoff, scientific databases have become a key factor in the organization of modern science. All the information and knowledge described in the novel scientific literature is translated into entries in many different scientific databases, making it possible to obtain very accurate information on a biological entity like genes or proteins without having to manually review the literature on it. However, even for the databases with the finest annotation procedures, errors or unclear parts sometimes appear in the publicly released version and influence the research of unaware scientists using them. The researcher that finds an error in a database is often left in a uncertain state, and often abandons the effort of reporting it because of a lack of a standard procedure to do so. In the present work, we propose that the simple adoption of a public error tracker application, as in many open software projects, could improve the quality of the annotations in many databases and encourage feedback from the scientific community on the data annotated publicly. In order to illustrate the situation, we describe a series of errors that we found and helped solve on the genes of a very well-known pathway in various biomedically relevant databases. We would like to show that, even if a majority of the most important scientific databases have procedures for reporting errors, these are usually not publicly visible, making the process of reporting errors time consuming and not useful. Also, the effort made by the user that reports the error often goes unacknowledged, putting him in a discouraging position

Reproducibility of patient setup by surface image registration system in conformal radiotherapy of prostate cancer

<p>Abstract</p> <p>Background</p> <p>The reproducibility of patient setup for radiotherapy is based on various methods including external markers, X-rays with planar or computerized image acquisition, and, more recently, surface matching imaging. We analyzed the setup reproducibility of 16 patients affected by prostate cancer who underwent conformal radiotherapy with curative intent by using a surface image registration system.</p> <p>Methods</p> <p>We analyzed the setup reproducibility of 16 patients affected by prostate cancer candidates for conformal radiotherapy by using a surface image registration system. At the initial setup, EPID images were compared with DRRs and a reference 3D surface image was obtained by the AlignRT system (Vision RT, London, UK). Surface images were acquired prior to every subsequent setup procedure. EPID acquisition was repeated when errors > 5 mm were reported.</p> <p>Results</p> <p>The mean random and systematic errors were 1.2 ± 2.3 mm and 0.3 ± 3.0 mm along the X axis, 0.0 ± 1.4 mm and 0.5 ± 2.0 mm along the Y axis, and 2.0 ± 1.8 mm and -0.7 ± 2.4 mm along the Z axis respectively. The positioning error detected by AlignRT along the 3 axes X, Y, and Z exceeded the value of 5 mm in 14.1%, 2.0%, and 5.1% measurements and the value of 3 mm in 36.9%, 13.6% and 27.8% measurements, respectively. Correlation factors calculated by linear regression between the errors measured by AlignRT and EPID ranged from 0.77 to 0.92 with a mean of 0.85 and SD of 0.13. The setup measurements by surface imaging are highly reproducible and correlate with the setup errors detected by EPID.</p> <p>Conclusion</p> <p>Surface image registration system appears to be a simple, fast, non-invasive, and reproducible method to analyze the set-up alignment in 3DCRT of prostate cancer patients.</p

CAS-MINE: Providing personalized services in context-aware applications by means of generalized rules

Context-aware systems acquire and exploit information on the user context to tailor services to a particular user, place, time, and/or event. Hence, they allowservice providers to adapt their services to actual user needs, by offering personalized services depending on the current user context. Service providers are usually interested in profiling users both to increase client satisfaction and to broaden the set of offered services. Novel and efficient techniques are needed to tailor service supply to the user (or the user category) and to the situation inwhich he/she is involved. This paper presents the CAS-Mine framework to efficiently discover relevant relationships between user context data and currently asked services for both user and service profiling. CAS-Mine efficiently extracts generalized association rules, which provide a high-level abstraction of both user habits and service characteristics depending on the context. A lazy (analyst-provided) taxonomy evaluation performed on different attributes (e.g., a geographic hierarchy on spatial coordinates, a classification of provided services) drives the rule generalization process. Extracted rules are classified into groups according to their semantic meaning and ranked by means of quality indices, thus allowing a domain expert to focus on the most relevant patterns. Experiments performed on three context-aware datasets, obtained by logging user requests and context information for three real applications, show the effectiveness and the efficiency of the CAS-Mine framework in mining different valuable types of correlations between user habits, context information, and provided services

A lightweight and open-source framework for the lifetime estimation of multicore systems

This paper presents a Monte Carlo-based framework for the estimation of lifetime reliability of multicore systems. Existing mathematical tools either consider only the time to the first failure, or are limited by their intrinsic complexity and high computational time. The proposed framework allows to compute quasi-exact results with a reasonable computational time, without adopting typical (and possibly misleading) simplifications that characterize the existing tools for computing Mean Time To Failure (MTTF). The paper describes the framework with all its mathematical details, assumptions and simplifications; it proves the correctness of the obtained results, by comparing them against the exact ones, and underlines the differences with the simplistic approaches, also discussing time overhead improvements

A system-level simulation framework for evaluating resource management policies for heterogeneous system architectures

Nowadays, heterogeneous system architectures, integrating CPUs and one or more kinds of accelerators (e.g., GPUs or HW accelerators), are a promising solution to achieve high performance for data-intensive workloads while fulfilling other system-level requirements on the available power/energy budgets. However, heterogeneity comes at the cost of greater design and management complexity leading to an increasing quest for the definition of innovative runtime resource management policies. We propose a system-level simulation framework implemented in SystemC and Transaction Level Modeling for a fast evaluation of resource management policies for such systems to provide a quick feedback to the middleware designer. A set of case studies shows the efficiency of the proposed framework in supporting a fast analysis of the investigated policies