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Tue, Apr 14, 8:00 PM IDT

One Chip Can't Do It All

The New AI Tech Stack

APU

GPU

TPU

LPU

Dan Eton_edited.png

Dan Eaton

CSO

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Bam Gobets

VP EMEA

Dani Voitsechov_edited.png

Dani Voitsechov

VP R&D, Co-Founder

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live_stream.png

Tue, Apr 14

One Chip Can't Do It All

The New AI Tech Stack
APU
GPU
TPU
LPU
Dan Eton_edited.png

Dan Eaton

CSO

bam_gobets.png

Bam Gobets

VP EMEA

Dani Voitsechov_edited.png

Dani Voitsechov

VP R&D, Co-Founder

AdobeStock_352079780-[Converted].png

meetup December 3-4

Meet us at HPE Discover Barcelona 

Early Access Intake
Early Access · Speedata Cloud

Speedata Accelerated Spark Service

Keep your data exactly where it lives - in AWS, Azure, and GCP - and offload your longest-running, costliest Spark jobs to the APU.

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$ 10,000

FREE APU HOURS

Up to $10,000 in free APU hours for qualified Early Access teams. Bring your heaviest Spark workload and see the acceleration on your own data.

How Early Access Works

No migration, no re-platforming. Your data never leaves your cloud.

01 · Keep
Data stays in your cloud

Your datasets remain in AWS, Azure, or GCP. Nothing moves, nothing gets copied out, and there are no egress charges.

02 · Point
Point to your Spark jobs

Identify your longest-running, most expensive Spark jobs and route them to the Accelerated Spark Service.

​

03 · Accelerate
The APU does the heavy lifting 

Speedata runs the heaviest stages in silicon, so the same jobs finish faster, at a fraction of the cost.

​

Why Teams Are Evaluating the APU

Purpose-built silicon for Apache Spark SQL, batch ETL, and AI data preparation.

259x*

Faster on TPC-H Q13 vs single-core SQL Server

100x

Faster on critical Spark workloads

90%

Lower total cost of ownership

37 → 7

Servers consolidated, slashing TCO

* TPC-H Q13 result measured and published by Microsoft, SIGMOD 2026.

Figures reflect Speedata published benchmarks for the C200 APU; actual results vary by workload.

Already Running Spark at Scale?

Get a deep-dive on how the APU fits your stack.

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