A Reconfigurable Vector Instruction Processor for Accelerating a Convection Parametrization Model on FPGAs

High Performance Computing (HPC) platforms allow scientists to model computationally intensive algorithms. HPC clusters increasingly use General-Purpose Graphics Processing Units (GPGPUs) as accelerators; FPGAs provide an attractive alternative to GPGPUs for use as co-processors, but they are still far from being mainstream due to a number of challenges faced when using FPGA-based platforms. Our research aims to make FPGA-based high performance computing more accessible to the scientific community. In this work we present the results of investigating the acceleration of a particular atmospheric model, Flexpart, on FPGAs. We focus on accelerating the most computationally intensive kernel from this model. The key contribution of our work is the architectural exploration we undertook to arrive at a solution that best exploits the parallelism available in the legacy code, and is also convenient to program, so that eventually the compilation of high-level legacy code to our architecture can be fully automated. We present the three different types of architecture, comparing their resource utilization and performance, and propose that an architecture where there are a number of computational cores, each built along the lines of a vector instruction processor, works best in this particular scenario, and is a promising candidate for a generic FPGA-based platform for scientific computation. We also present the results of experiments done with various configuration parameters of the proposed architecture, to show its utility in adapting to a range of scientific applications.Comment: This is an extended pre-print version of work that was presented at the international symposium on Highly Efficient Accelerators and Reconfigurable Technologies (HEART2014), Sendai, Japan, June 911, 201

What caused the cool summer over northern Central Asia, East Asia and central North America during 2009?

Cool and wet weather conditions hit northern Central Asia, East Asia and central North America during the 2009 summer in concert with a strong jet stream and a prominent meandering upper-level circulation in the Northern Hemisphere mid-latitudes despite the fact that the year 2009 is the fifth warmest year globally in the modern record. It is found that the conspicuous atmospheric variability in the entire Northern Hemisphere mid-latitudes during the summer of 2009 was caused by a combination of teleconnections associated with significant tropical thermal forcings, strong polar forcing, and interaction between high-frequency weather events and climate anomalies. The strong negative circumglobal teleconnection pattern associated with the deficient Indian summer monsoon rainfall and developing El Niño condition was the major contributor to the cool and wet summer in June. On the other hand, the July weather conditions were attributable to the high-latitude impact of the unprecedented negative Arctic Oscillation, together with the Rossby wave response to the subtropical heating generated by convective activities over the Western North Pacific summer monsoon region. It is also noted that enhanced storm track activity and frequent cold surges from high-latitudes may have played a role in the cool and wet summer over the regions of interest

Impact of a narrow coastal Bay of Bengal sea surface temperature front on an Indian summer monsoon simulation

A dry bias in climatological Central Indian rainfall plagues Indian summer monsoon (ISM) simulations in multiple generations of climate models. Here, using observations and regional climate modeling, we focus on a warm coastal Bay of Bengal sea surface temperature (SST) front and its impact on Central Indian rainfall. The SST front, featuring sharp gradients as large as 0.5 °C/100 km, is colocated with a mixed layer depth (MLD) front, in a region where salinity variations are known to control MLD. Regional climate simulations coupling a regional atmospheric model with an ocean mixed layer model are performed. A simulation with observed MLD climatology reproduces SST, rainfall, and atmospheric circulation associated with ISM reasonably well; it also eliminates the dry bias over Central India significantly. Perturbing MLD structure in the simulations, we isolate the SST front’s impact on the simulated ISM climate state. This experiment offers insights into ISM climatological biases in the coupled NCEP Climate Forecast System version-2. We suggest that the warm SST front is essential to Central Indian rainfall as it helps to sustain deep and intense convection in its vicinity, which may be a source for the vortex cores seeding the monsoon low-pressure systems.Published versio