Related papers: VSC-WebGPU: A Selenium-based VS Code Extension For…
The rapid growth of deep learning has driven exponential increases in model parameters and computational demands. NVIDIA GPUs and their CUDA-based software ecosystem provide robust support for parallel computing, significantly alleviating…
Edge-cloud computing offloads parts of the computations that traditionally occurs in the cloud to edge nodes,e.g., CDN servers, in order to get closer to the users and reduce latency. To improve performance even further, WebAssembly is…
GPUs and other accelerators are popular devices for accelerating compute-intensive, parallelizable applications. However, programming these devices is a difficult task. Writing efficient device code is challenging, and is typically done in…
The Vega grammar has been broadly adopted by a growing ecosystem of browser-based visualization tools. However, the reference Vega renderer does not scale well to large datasets (e.g., millions of rows or hundreds of megabytes) because it…
The emergence of large language models has enabled vibe coding, a natural language approach to programming in which users describe intent and AI generates or revises code, potentially broadening access to programming while preserving…
Cloud computing and Network Function Virtualization (NFV) are emerging as key technologies to overcome the challenges facing 4G and beyond mobile systems. Over the last few years, Platform-as-a-Service (PaaS) has gained momentum and has…
Hardware/Software (HW/SW) co-designed processors provide a promising solution to the power and complexity problems of the modern microprocessors by keeping their hardware simple. Moreover, they employ several runtime optimizations to…
The automation of user interface development has the potential to accelerate software delivery by mitigating intensive manual implementation. Despite the advancements in Large Multimodal Models for design-to-code translation, existing…
Graphics processing units (GPUs) excel at parallel processing, but remain largely unexplored in ultra-low-power edge devices (TinyAI) due to their power and area limitations, as well as the lack of suitable programming frameworks. To…
The wider adoption of tightly coupled core-adjacent accelerators, such as Arm Scalable Matrix Extension (SME), hinges on lowering software programming complexity. In this paper, we focus on enabling the use of SME architecture in Streaming…
Developing an algorithm for a visualization prototype often involves the direct comparison of different development stages and design decisions, and even minor modifications may dramatically affect the results. While existing development…
User interface (UI) development requires translating design mockups into functional code, a process that remains repetitive and labor-intensive. While recent Vision-Language Models (VLMs) automate UI-to-Code generation, they generate only…
Utilizing GPUs is critical for high performance on heterogeneous systems. However, leveraging the full potential of GPUs for accelerating legacy CPU applications can be a challenging task for developers. The porting process requires…
Modern platforms used for high-performance computing (HPC) include machines with both general-purpose CPUs, and "accelerators", often in the form of graphical processing units (GPUs). StarPU is a C library to exploit such platforms. It…
GPU accelerators have had a notable impact on high-performance computing across many disciplines. They provide high performance with low cost/power, and therefore have become a primary compute resource on many of the largest supercomputers.…
Machine learning algorithms must be able to efficiently cope with massive data sets. Therefore, they have to scale well on any modern system and be able to exploit the computing power of accelerators independent of their vendor. In the…
Methods developed at the Texas Advanced Computing Center (TACC) are described and demonstrated for automating the construction of an elastic, virtual cluster emulating the Stampede2 high performance computing (HPC) system. The cluster can…
A large part of modern research, especially in the broad field of complex systems, relies on the numerical integration of PDEs, with and without stochastic noise. This is usually done with eiher in-house made codes or external packages like…
To execute scientific computing programs such as deep learning at high speed, GPU acceleration is a powerful option. With the recent advancements in web technologies, interfaces like WebGL and WebGPU, which utilize GPUs on the client side…
Visualizations have become an indispensable part of the scientific process. A vibrant ecosystem of visualization tools exists, catering to a wide variety of different needs. Real-time visualizations of numerical simulations offer scientists…