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The Analytics Acceleration Blog
Featured Articles


259× Faster! What Microsoft's Award-Winning SIGMOD Paper Says About the Speedata APU
Microsoft's paper "CoddSpeed: Hardware Accelerated Query Processing in Microsoft Fabric" won the Best Industry Paper Award at SIGMOD 2026, one of the top academic conferences in database research. The paper documents Microsoft's multi-year effort to move analytics from CPUs onto hardware accelerators and the Speedata C-200 Analytics Processing Unit (APU) is one of the three coprocessor architectures Microsoft integrated and benchmarked inside its next-generation Fabric archit

Daniela Sztulwark
4 days ago3 min read


259× Faster! What Microsoft's Award-Winning SIGMOD Paper Says About the Speedata APU
Microsoft's paper "CoddSpeed: Hardware Accelerated Query Processing in Microsoft Fabric" won the Best Industry Paper Award at SIGMOD 2026, one of the top academic conferences in database research. The paper documents Microsoft's multi-year effort to move analytics from CPUs onto hardware accelerators and the Speedata C-200 Analytics Processing Unit (APU) is one of the three coprocessor architectures Microsoft integrated and benchmarked inside its next-generation Fabric archit

Daniela Sztulwark
4 days ago3 min read


Know Your Unknowns: Building Knowledge Bases for Your VLSI Engineering Organization (Practical Rules)
Practical guidelines for making AI coding agents work in real VLSI design environments, skills, context, traceability, and the human-only decisions.

Adi Fuchs
May 123 min read


One Chip Can’t Do It All - The New AI Tech Stack
No single processor can handle every AI workload efficiently. Speedata's recap breaks down how CPUs, GPUs, TPUs, LPUs, and APUs each fit into the modern AI infrastructure stack.

Daniela Sztulwark
Apr 147 min read


Embedding AI in Chip Development: Challenges and Opportunities
RTL is crown-jewel IP, hardware assigns concurrently not sequentially, and most enterprise GenAI pilots are failing. The software AI playbook doesn't transfer to chip design — the training data isn't there, the semantics don't map. Here's what it actually takes to embed AI into chip development workflows.

Adi Fuchs
Mar 66 min read


The Future of Intelligent Systems: The Intersection of Silicon, Data and AI
As technology advances at a staggering pace, the world is bracing for a multi-trillion-dollar economic transformation unlike anything we’ve seen before. At the center of this shift is the rise of intelligent systems, along with the massive compute infrastructure required to power them. These systems mark a real break from the technological rules we’ve grown used to - they don’t run on compute alone, but on a three-part foundation of compute, intelligence, and data. You don’t

Adi Fuchs
Feb 116 min read


From Merge Sort to Silicon: Why We Had to Rethink Computer Science
What if the algorithms we learned in computer science were designed for the wrong hardware? At Speedata, we're not just writing software. We're co-designing the silicon itself. When our sorting problem hit the limits of existing approaches, we walked into the room next door and worked with our chip architects to create a new solution.

Boaz Menuhin
Jan 303 min read


Webinar Recap: The New Computing Paradigm for Advanced Analytics & AI
CPUs and GPUs weren't built for analytics at scale. See how purpose-built processors for analytics workloads delivers 11x faster Apache Spark performance, with real results from pharma and adtech deployments, and a free Workload Analyzer to test against your own jobs.

Daniela Sztulwark
Dec 10, 20253 min read
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