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Posts

Aug, 29

The Art of Balance: A RateupDB Experience of Building a CPU/GPU Hybrid Database Product

GPU-accelerated database systems have been studied for more than 10 years, ranging from prototyping development to industry products serving in multiple domains of data applications. Existing GPU database research solutions are often focused on specific aspects in parallel algorithms and system implementations for specific features, while industry product development generally concentrates on delivering a whole […]
Aug, 29

Performance Portability and Evaluation of Heterogeneous Components of SeisSol Targeted to Upcoming Intel HPC GPUs

For the first time in over 20 years, Intel is selling discrete graphics cards, including products for high-performance computing, scheduled for release in 2022. This thesis investigates programming models for the upcoming Intel GPUs and selects the Sycl standard, provided by oneAPI and hipSYCL, to port the heterogeneous components of SeisSol. The modules in question […]
Aug, 29

GRIM: A General, Real-Time Deep Learning Inference Framework for Mobile Devices based on Fine-Grained Structured Weight Sparsity

It is appealing but challenging to achieve real-time deep neural network (DNN) inference on mobile devices because even the powerful modern mobile devices are considered as "resource-constrained" when executing large-scale DNNs. It necessitates the sparse model inference via weight pruning, i.e., DNN weight sparsity, and it is desirable to design a new DNN weight sparsity […]
Aug, 22

EXA2PRO: A Framework for High Development Productivity on Heterogeneous Computing Systems

Programming upcoming exascale computing systems is expected to be a major challenge. New programming models are required to improve programmability, by hiding the complexity of these systems from application developers. The EXA2PRO programming framework aims at improving developers productivity for applications that target heterogeneous computing systems. It is based on advanced programming models and abstractions […]
Aug, 22

perf4sight: A toolflow to model CNN training performance on Edge GPUs

The increased memory and processing capabilities of today’s edge devices create opportunities for greater edge intelligence. In the domain of vision, the ability to adapt a Convolutional Neural Network’s (CNN) structure and parameters to the input data distribution leads to systems with lower memory footprint, latency and power consumption. However, due to the limited compute […]
Aug, 22

Parallel time integration using Batched BLAS (Basic Linear Algebra Subprograms) routines

We present an approach for integrating the time evolution of quantum systems. We leverage the computation power of graphics processing units (GPUs) to perform the integration of all time steps in parallel. The performance boost is especially prominent for small to medium-sized quantum systems. The devised algorithm can largely be implemented using the recently-specified batched […]
Aug, 22

Performance comparison of CFD-DEM solver MFiX-Exa, on GPUs and CPUs

We present computational performance comparisons of gas-solid simulations performed on current CPU and GPU architectures using MFiX Exa, a CFD-DEM solver that leverages hybrid CPU+GPU parallelism. A representative fluidized bed simulation with varying particle numbers from 2 to 67 million is used to compare serial and parallel performance. A single GPU was observed to be […]
Aug, 22

Better GPU Hash Tables

We revisit the problem of building static hash tables on the GPU and design and build three bucketed hash tables that use different probing schemes. Our implementations are lock-free and offer efficient memory access patterns; thus, only the probing scheme is the factor affecting the performance of the hash table’s different operations. Our results show […]
Aug, 8

ndzip-gpu: Efficient Lossless Compression of Scientific Floating-Point Data on GPUs

Lossless data compression is a promising software approach for reducing the bandwidth requirements of scientific applications on accelerator clusters without introducing approximation errors. Suitable compressors must be able to effectively compact floating-point data while saturating the system interconnect to avoid introducing unnecessary latencies. We present ndzip-gpu, a novel, highly-efficient GPU parallelization scheme for the block […]
Aug, 8

Performance assessment of CUDA and OpenACC in large scale combustion simulations

GPUs have climbed up to the top of supercomputer systems making life harder to many legacy scientific codes. Nowadays, many recipes are being used in such code’s portability, without any clarity of which is the best option. We present a comparative analysis of the two most common approaches, CUDA and OpenACC, into the multi-physics CFD […]
Aug, 8

On Efficient GPGPU Computing for Integrated Heterogeneous CPU-GPU Microprocessors

Heterogeneous microprocessors which integrate a CPU and GPU on a single chip provide low-overhead CPU-GPU communication and permit sharing of on-chip resources that a traditional discrete GPU would not have direct access to. These features allow for the optimization of codes that heretofore would be suitable only for multi-core CPUs or discrete GPUs to be […]
Aug, 8

ScaleHLS: Scalable High-Level Synthesis through MLIR

High-level Synthesis (HLS) has been widely adopted as it significantly improves the hardware design productivity and enables efficient design space exploration (DSE). HLS tools can be used to deliver solutions for many different kinds of design problems, which are often better solved with different levels of abstraction. While existing HLS tools are built using compiler […]

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