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Thomas Graves

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Principal Systems Software Engineer NVIDIA

Thomas Graves is a distributed systems software engineer at NVIDIA, where he concentrates on accelerating Spark. He is a committer and PMC on Apache Spark and Apache Hadoop. Previously worked for Yahoo on the Big Data Platform team working on Apache Spark, Hadoop, YARN, Storm, and Kafka.

Bio from: Data + AI Summit 2025

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Tracing the Path of a Row Through a GPU-Enabled Query Engine on the Grace-Blackwell Architecture

Grace-Blackwell is NVIDIA’s most recent GPU system architecture. It addresses a key concern of query engines: fast data access. In this session, we will take a close look at how GPUs can accelerate data analytics by tracing how a row flows through a GPU-enabled query engine.Query engines read large data from CPU memory or from disk. On Blackwell GPUs, a query engine can rely on hardware-accelerated decompression of compact formats. The Grace-Blackwell system takes data access performance even further, by reading data at up to 450 GB/s across its CPU to GPU interconnect. We demonstrate full end-to-end SQL query acceleration using GPUs in a prototype query engine using industry standard benchmark queries. We compare the results to existing CPU solutions.Using Apache Spark™ and the RAPIDS Accelerator for Apache Spark, we demonstrate the impact GPU acceleration has on the performance of SQL queries at the 100TB scale using NDS, a suite that simulates real-world business scenarios.