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Optimized Code Generation for Parallel and Polyhedral Loop Nests using MLIR
In this thesis we show the benefits of the novel MLIR compiler technology to the generation of code from a DSL, namely EasyML used in openCARP, a widely used simulator in the cardiac electrophysi...
Deep Learning and Machine Learning with GPGPU and CUDA: Unlocking the Power of Parallel Computing
This book presents a comprehensive exploration of GPGPU (General Purpose Graphics Processing Unit) and its applications in deep learning and machine learning. It focuses on how parallel computing...
Sound and Partially-Complete Static Analysis of Data-Races in GPU Programs
GPUs are progressively being integrated into modern society, playing a pivotal role in Artificial Intelligence and High-Performance Computing. Programmers need a deep understanding of the GPU pro...
A domain-specific language for geospatial computations on the GPU
This thesis explores how a domain-specific language (DSL) for simple geospatial operators on the GPU can be developed, and evaluates the level of functionality and performance of such a DSL. The ...
Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation
In recent years, the need for high-performance computing solutions has increased due to the growing complexity of computational tasks. The use of parallel processing techniques has become essenti...
Understanding Data Movement in AMD Multi-GPU Systems with Infinity Fabric
Modern GPU systems are constantly evolving to meet the needs of computing-intensive applications in scientific and machine learning domains. However, there is typically a gap between the hardware...
Efficient Arbitrary Precision Acceleration for Large Language Models on GPU Tensor Cores
Large language models (LLMs) have been widely applied but face challenges in efficient inference. While quantization methods reduce computational demands, ultra-low bit quantization with arbitrar...
Event-Based OpenMP Tasks for Time-Sensitive GPU-Accelerated Systems
The throughput-centric design of GPUs poses challenges when integrating them into time-sensitive applications. Nevertheless, modern GPU architectures and software have recently evolved, making it...
Benchmarking Thread Block Cluster
Graphics processing units (GPUs) have become essential accelerators in the fields of artificial intelligence (AI), high-performance computing (HPC), and data analytics, offering substantial perfo...
Intel(R) SHMEM: GPU-initiated OpenSHMEM using SYCL
Modern high-end systems are increasingly becoming heterogeneous, providing users options to use general purpose Graphics Processing Units (GPU) and other accelerators for additional performance. ...