CPU

Your Apple Silicon GPU Loses to One CPU Core Until a Million Rows. I Measured 111 Operations, Then Rebuilt ArrowMetal 0.2.0 Around the Answer

Every GPU data library benchmarks itself at 50 million rows. Your dataframe has 80,000. On an Apple M4 Max, summing 1,000 integers takes the GPU 112 microseconds and Polars less than one: the GPU is more than 100 times behind. I built one of these libraries, so I measured the row count where the GPU overtakes the fastest CPU code for 111 operations: the median needs 10,000,000 rows against a multi-core library, about a million against one core, and sixteen never get there. So ArrowMetal 0.2.0 refuses the GPU below the line, byte-identical, and around that router it grew GPU readers for CSV, JSON, nested Parquet, Delta Lake and Iceberg, a Polars engine and a DuckDB optimizer extension.