The Era of the GPU is Here

A world transformed. 

• Urban landscapes where traffic is seamlessly managed by AI systems processing real-time data. 
• Healthcare personalized in moments based on the analysis of genetic data from millions. 
• Agricultural drones and sensors ensuring food security for a growing global population. 

This isn’t science fiction. It’s the very near future, made possible by a tectonic shift in data technology – the graphics processing unit (GPU) – which is rapidly redefining what’s possible. 

From CPU to GPU

Before the GPU there was the central processing unit (CPU), the brain of the computer, introduced by Intel in 1971. This little chip gave birth to a new industry. Its linear, step-by-step processing power drove the design of mainframes, personal and enterprise computers, databases, and software. Even cloud platforms were initially created with CPU-based tools and infrastructure. 

The incredibly rapid development of computing capabilities led to a demand for faster and smarter graphics, which strained CPUs and slowed down performance. The solution was a separate unit – the GPU – with parallel processing capabilities to take over complex graphics-related calculations and free the CPU to handle everything else. 

The GPU is a leap in computing power that promises to be as transformative as the rise of the CPU. 

The GPU: From Apps to AI

Initially developed to improve gaming, GPUs later turned up at the forefront of cryptocurrency mining because of their capability to carry out many calculations simultaneously. This also makes them perfect for big data analytics and artificial intelligence (AI), which requires processing and analyzing vast datasets at incredible speeds.

But GPUs provide much more than just faster data processing. They enable real-time analytics, machine learning at scale, and leveraging the exponential growth of data in ways we’re only beginning to grasp. 

GPU-based data processing has already begun to impact innovation in consumer applications, business-to-business services and products, cloud data centers, and AI development. The build-out of data centers to accommodate the needs of generative AI, for example, has led to an increased demand for NVIDIA’s GPUs. 

These days, NVIDIA is partnering with leading computer manufacturers to build AI factories and data centers, heralding the next industrial revolution. These AI factories, powered by the NVIDIA Blackwell architecture, are transforming traditional data centers into high-efficiency, AI-driven hubs. This shift enables unprecedented data processing capabilities and advances in AI, driving innovation and efficiency across industries. 

The potential of GPUs has been unleashed, a whole new economy is on the way, and it seems that the sky’s the limit. 

Almost. 

The Cost of Greater Capabilities

Smart business decisions are based on insights from enterprise data, which is proliferating at an unprecedented rate. That means the need for speed and efficiency in analytics, machine learning, and artificial intelligence projects has never been greater. 

While GPUs significantly boost performance compared to CPU-only solutions, companies still struggle with lengthening waits and an ever-increasing spend when analyzing or querying expanding raw datasets. Even with the incorporation of GPUs in their data stack infrastructure, enterprises need faster results at a more reasonable cost.

SQream: For the Entire Data Workflow

SQream brings enterprises a clear-cut, measurable, consistent, and significant improvement in cost-effectiveness across the data workflow. It combines blazing-fast performance with a minimal hardware footprint, simplicity and effortless scaling. 

SQream was designed to handle intensive workloads, accelerating data processing end to end: 

• Preparation
• Transformation
• Movement
• Analytics
• ML models

With SQream’s innovative GPU-based technology, processes that took days are reduced to minutes, tasks that required hours are done in seconds. Complex queries across billions of records are completed in the blink of an eye, empowering your data scientists and analysts to unlock insights faster and more efficiently than ever before. 

Pay Less, Analyze More

The SQream data and analytics platform is built from the ground up as a native multicore and GPU solution. Uniquely combining parallelism on separate nodes and on a single GPU chip (MPP-on-chip), SQream’s acceleration is simultaneous, not sequential. A single node hosting multiple GPUs increases concurrency even further, with decoupled storage and compute and rapid metadata standardization ensuring that data and analysis are always fresh. 

SQream seamlessly integrates with your existing data stack, running in the cloud or on-prem, making it an effortless addition to any data infrastructure – all while reducing your carbon footprint.

Over a decade ago, SQream spotted the untapped potential of GPUs. While the tech world is now awakening to this reality, SQream is already opening up new horizons and preparing you for the future of data. 

Meet our Co-Founder & CEO, Ami Gal: