Providing Insight into the Performance of Distributed Applications Through Low-Level Metrics

The field of high-performance computing (HPC) has always dealt with the bleeding edge of computational hardware and software to achieve the maximum possible performance for a wide variety of workloads. When dealing with brand new technologies, it can be difficult to understand how these technologies work and why they work the way they do. One of the more prevalent approaches to providing insight into modern hardware and software is to provide tools that allow developers to access low-level metrics about their performance. The modern HPC ecosystem supports a wide array of technologies, but in this work, I will be focusing on two particularly influential technologies: The Message Passing Interface (MPI), and Graphical Processing Units (GPUs).For many years, MPI has been the dominant programming paradigm in HPC. Indeed, over 90% of applications that are a part of the U.S. Exascale Computing Project plan to use MPI in some fashion. The MPI Standard provides programmers with a wide variety of methods to communicate between processes, along with several other capabilities. The high-level MPI Profiling Interface has been the primary method for profiling MPI applications since the inception of the MPI Standard, and more recently the low-level MPI Tool Information Interface was introduced.Accelerators like GPUs have been increasingly adopted as the primary computational workhorse for modern supercomputers. GPUs provide more parallelism than traditional CPUs through a hierarchical grid of lightweight processing cores. NVIDIA provides profiling tools for their GPUs that give access to low-level hardware metrics.In this work, I propose research in applying low-level metrics to both the MPI and GPU paradigms in the form of an implementation of low-level metrics for MPI, and a new method for analyzing GPU load imbalance with a synthetic efficiency metric. I introduce Software-based Performance Counters (SPCs) to expose internal metrics of the Open MPI implementation along with a new interface for exposing these counters to users and tool developers. I also analyze a modified load imbalance formula for GPU-based applications that uses low-level hardware metrics provided through nvprof in a hierarchical approach to take the internal load imbalance of the GPU into account

Table2Vec: Neural Word and Entity Embeddings for Table Population and Retrieval

Tables contain valuable knowledge in a structured form. We employ neural language modeling approaches to embed tabular data into vector spaces. Specifically, we consider different table elements, such caption, column headings, and cells, for training word and entity embeddings. These embeddings are then utilized in three particular table-related tasks, row population, column population, and table retrieval, by incorporating them into existing retrieval models as additional semantic similarity signals. Evaluation results show that table embeddings can significantly improve upon the performance of state-of-the-art baselines.Comment: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '19), 201

Effect of arsenic-phosphorus interaction on arsenic-induced oxidative stress in chickpea plants

Arsenic-induced oxidative stress in chickpea was investigated under glasshouse conditions in response to application of arsenic and phosphorus. Three levels of arsenic (0, 30 and 60 mg kg−1) and four levels of P (50, 100, 200, and 400 mg kg−1) were applied to soil-grown plants. Increasing levels of both arsenic and P significantly increased arsenic concentrations in the plants. Shoot growth was reduced with increased arsenic supply regardless of applied P levels. Applied arsenic induced oxidative stress in the plants, and the concentrations of H2O2 and lipid peroxidation were increased. Activity of superoxide dismutase (SOD) and concentrations of non-enzymatic antioxidants decreased in these plants, but activities of catalase (CAT) and ascorbate peroxidase (APX) were significantly increased under arsenic phytotoxicity. Increased supply of P decreased activities of CAT and APX, and decreased concentrations of non-enzymatic antioxidants, but the high-P plants had lowered lipid peroxidation. It can be concluded that P increased uptake of arsenic from the soil, probably by making it more available, but although plant growth was inhibited by arsenic the P may have partially protected the membranes from arsenic-induced oxidative stress

The quantitative LIF determination of OH concentrations in low-pressure flames

Kohse-Höinghaus K, Jeffries JB, Copeland RA, Smith GP, Crosley DR. The quantitative LIF determination of OH concentrations in low-pressure flames. PROCEEDINGS OF THE COMBUSTION INSTITUTE. 1989;22(1):1857-1866.Laser-induced fluorescence (LIF) of OH is used to measure spatially resolved temperature and concentration profiles in premixed laminar flames of H2 burning in mixtures of O2 and N2O at 7.2 Torr. Potential sources of error in such measurements are investigated: optical depth; the detector spectral bias, time delay, and sampling gate; and rotational level dependence of the quantum yield for the OH radical. We explicitly demonstrate differences between LIF intensity measurements and the actual OH concentration profiles caused by the temperature dependence of the rotational level populations across the flame front. By varying the proportion of O2 and N2O in stoichiometric flames, burnt gas temperatures between 1200 and 2300K are obtained. Quenching measurements in the burnst gases of these flames show that quenching by atomic hydrogen can be important. In the burnt gases of the H2/N2O flame, the quenching does not significantly depend on rotational level for diagnostics with 5% accuracy. However, in the chemically interesting and important flame front, there is a significant variation in the quantum yield with rotational level, and in the flame front of atmospheric pressure flames such quantum yield corrections are likely to be important

The quantitative LIF determination of OH concentrations in low-pressure flames

Kohse-Höinghaus K, Jeffries JB, Copeland RA, Smith GP, Crosley DR. The quantitative LIF determination of OH concentrations in low-pressure flames. PROCEEDINGS OF THE COMBUSTION INSTITUTE. 1989;22(1):1857-1866.Laser-induced fluorescence (LIF) of OH is used to measure spatially resolved temperature and concentration profiles in premixed laminar flames of H2 burning in mixtures of O2 and N2O at 7.2 Torr. Potential sources of error in such measurements are investigated: optical depth; the detector spectral bias, time delay, and sampling gate; and rotational level dependence of the quantum yield for the OH radical. We explicitly demonstrate differences between LIF intensity measurements and the actual OH concentration profiles caused by the temperature dependence of the rotational level populations across the flame front. By varying the proportion of O2 and N2O in stoichiometric flames, burnt gas temperatures between 1200 and 2300K are obtained. Quenching measurements in the burnst gases of these flames show that quenching by atomic hydrogen can be important. In the burnt gases of the H2/N2O flame, the quenching does not significantly depend on rotational level for diagnostics with 5% accuracy. However, in the chemically interesting and important flame front, there is a significant variation in the quantum yield with rotational level, and in the flame front of atmospheric pressure flames such quantum yield corrections are likely to be important