Improving GPGPU Performance with Cooperative Thread Array Scheduling Techniques
Limited DRAM bandwidth poses a critical bottleneck in GPU performance, necessitating a comprehensive scheduling policy to reduce cache miss rates, enhance DRAM bandwidth, and improve latency hiding for GPUs. The CTA-aware scheduling techniques presented address these challenges by optimizing resourc
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Exploring Challenges and Opportunities in Processing-in-Memory Architecture
PIM technology aims to enhance performance by moving computation closer to memory, improving bandwidth, latency, and energy efficiency. Despite initial setbacks, new strategies focus on cost-effectiveness, programming models, and overcoming implementation challenges. A new direction proposes intuiti
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Managing DRAM Latency Divergence in Irregular GPGPU Applications
Addressing memory latency challenges in irregular GPGPU applications, this study explores techniques like warp-aware memory scheduling and GPU memory controller optimization to reduce DRAM latency divergence. The research delves into the impact of SIMD lanes, coalescers, and warp-aware scheduling on
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A Performance Analysis Framework for GPGPU Applications
This framework, GPUPerf, focuses on identifying potential benefits in GPGPU applications through performance analysis, modeling, and user-friendly metrics. It addresses the challenges programmers face in optimizing GPGPU code, providing guidance on program analysis and performance modeling. The fram
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Accelerated Computing Activity Progress Report at EGI Conference 2016
This report outlines the progress made in implementing a new accelerated computing platform as part of the EGI-Engage JRA2 project. The project aimed to support GPGPU integration in batch systems and disciplines like structural biology and molecular dynamics. Key performance indicators and work plan
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Enhancing GPGPU Performance through Inter-Warp Heterogeneity Exploitation
This research focuses on addressing memory divergence issues in GPGPUs by exploiting inter-warp heterogeneity. By prioritizing mostly-hit warps and deprioritizing mostly-miss warps through Memory Divergence Correction (MeDiC), significant performance and energy efficiency improvements were achieved
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Emerging Trends in Bioinformatics: Leveraging CUDA and GPGPU
Today, the intersection of science and technology drives advancements in bioinformatics, enabling the analysis and visualization of vast data sets. With the utilization of CUDA programming and GPGPU technology, researchers can tackle complex problems efficiently. Massive multithreading and CUDA memo
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Understanding Depth of Field Effects in Rendering
Depth of Field (DOF) refers to the range between the nearest and farthest objects in an image that appear sharp. This article explores DOF effects in rendering, multipass approaches in graphics, and current progress in developing depth-variant filters for enhancing image clarity and focus. The goals
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Accelerated Computing in EGI Federated Cloud
This document discusses the implementation of GPGPU technology in cloud computing, focusing on enabling technologies, cloud middleware frameworks, and a specific GPU-enabled site called IISAS-GPUCloud. It covers virtualization technologies, container-based technologies, and details about the hardwar
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