The Analytics Processing Unit (APU) — purpose-built silicon for AI data prep, Apache Spark SQL & batch ETL. 100x faster. 90% lower TCO. Zero code changes.
- Tweets87
- Following147
- Followers83
- Likes51
ALT Get up to $10,000 in free APU hours. Bring your heaviest workload and see the acceleration on your own data. Sign up for early access to Speedata's Accelerated Spark Service. Offload your heaviest Apache Spark jobs to the Analytics Processing Unit (APU) and cut the cost of running them by up to 99%. Your data stays exactly where it lives, in Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform, on the platforms you already run like Databricks, AWS (EMR, Athena, Glue), Microsoft Fabric, and Cloudera. Your longest-running Spark jobs are your most expensive ones. They don't have to be. Request Early Access, limited spots. https://www.speedata.io/spark-early-access
ALT How much faster would your Spark workloads run on dedicated analytics silicon? The Speedata Workload Analyzer projects how much faster your real analytics or AI data prep pipelines would run on the Analytics Processing Unit (APU). Three ways to test: 🟧 Upload a Spark event log in the browser - results in minutes 🟧 Run our CLI locally - your logs never leave your environment 🟧 Compare against TPC-DS benchmarks Real analytics pipelines, projected against the Analytics Processing Unit (APU). Try our Workload Analyzer: https://tinyurl.com/SpeedataWorkloadAnalyzer #AnalyticsAcceleration #CloudCost #FinOps #AIDataPrep #MLOps #Semiconductors #AI #CPU #GPU
ALT Why does a GPU running SQL feel like it's barely trying? Why are TPUs cloud-only? What does an LPU actually do that a GPU can't? The architectures are different because the workloads are different, and at production scale, those differences compound into real money. A breakdown of the five processors defining modern compute, and where each one fits https://www.speedata.io/post/apu-vs-lpu-vs-tpu-vs-gpu-vs-cpu-when-to-use-each-one #semiconductors #AI #APU #CPU #TPU #LPU #GPU #Nvidia #Google
ALT The Speedata analytics processing unit (APU) is purpose-built silicon for Apache Spark analytics acceleration, and every Wednesday we host a live session for anyone who wants to see it in action. We spend 20 minutes running Spark SQL or AI data prep workloads on the APU and walking through the architecture, then open up the final 10 minutes for live Q&A. Sessions alternate between 10am PDT and 10am CEST so it works whichever side of the Atlantic you're on. Pick a Wednesday. Link to register: https://www.speedata.io/live-apu-demo #AI #SQL #Spark #gpu #semiconductor
