- GPU Computing
What Is A GPU Spreadsheet? A Complete Guide
A GPU spreadsheet uses the graphics processor to calculate faster at larger scale. See how it works, how it compares to a Python spreadsheet, and examples.
- GPU Computing
The Enemies of Performance
The increasing volume of data and advancements in computer hardware have created a significant challenge for businesses: processing and visualizing data efficiently. Despite the availability of powerful hardware, conventional dashboards often experience bottlenecks and slowdowns under high pressure. This is largely due to inefficient code and legacy architectures in visualization platforms. The era of relying solely on hardware improvements for speed gains is limited, as software inefficiencies can negate these benefits. Modern software development often prioritizes hardware improvements over performance coding, leading to missed opportunities for optimization. Legacy database code, developed for older hardware, struggles to integrate new performance technologies, making it difficult to achieve perfect optimization. Row64, a real-time visual business intelligence platform, addresses these challenges by employing modern performance principles and leveraging high-performance hardware. Its founding team, with a background in game technology, prioritizes performance and takes advantage of chip advancements to achieve high frame rates. Row64's custom stack, built from the ground up for maximum speed and scalability, taps into the full potential of modern hardware. The company has identified four major enemies of performance in streaming and dashboard software: memory allocation, cache misses, ignoring hardware, and garbage collection. Memory allocation is slow, and repeated requests and releases of memory incur a time penalty. Cache misses occur when the CPU requests data not present in cache, leading to slower searches through the memory hierarchy. Ignoring hardware opportunities, such as parallelization, GPU utilization, and caching optimizations, can also hinder performance. Garbage collection, while convenient, can introduce performance penalties and memory fragmentation. To combat these enemies, Row64 employs a unified memory approach, where data is vertically integrated, centralized, contiguous, and hardware-driven. Its vertically-integrated stack components share the same memory layout, reducing the need for copies and unnecessary memory allocation. Row64's data format, ByteStream, is optimized for contiguous memory, minimizing cache misses. The platform also utilizes a RAM database, RamDB, designed for high-speed data access and manipulation. Row64's Hybrid Engine adapts to underlying hardware, using optimal resources and providing a direct connection to the hardware. The platform is highly threaded and parallelized on both CPU and GPU, utilizing all available cores and parallelizing network communications and requests. By addressing the challenges of data processing and visualization, Row64 aims to elevate the standards for a new generation of dashboards and data visualization. Its design allows for high-speed data visualization, live streaming updates, and multi-tenancy, making it well-positioned to meet the growing demands of the industry.
- GPU Computing
Data Center CPU Trends
As the artificial intelligence (AI) sector experiences rapid growth, the spotlight on data center hardware has largely been on Graphics Processing Units (GPUs). However, a closer examination reveals several significant trends with Central Processing Units (CPUs) that will fundamentally impact how software applications are created and deployed. A new video delves into these trends, shedding light on their potential implications for the development and rollout of software applications.
- GPU Computing
Integrated GPUs and the Rise of the GPU Dashboard
WebGL, has enabled high-quality graphics rendering and interaction in web browsers without plugins. WebGL 2.0, integrated GPUs, and browser updates have unleashed unprecedented browser-based visual quality and performance. This enables data exploration, visual analysis, and real-time tracking across various domains, making it accessible to diverse audiences.
- GPU Computing
GPU Selection is Revolutionizing Dashboards
Row64's real-time visual analytics enables companies to efficiently analyze large data sets, allowing users to drill down to record-level detail instantly. This eliminates the need for manual summarization or program integration, saving time and resources. The company demonstrates this capability with use cases in power grid management, demographic research, and organizational chart analysis, showcasing the vast potential of real-time data for businesses.