Beyond the Vector API – A Quest for a Lower Level API [JVMLS] (inside.java)

At JVMLS 2025 Vladimir Ivanov argued that Java needs a lower-level “hardware intrinsics” API to complement the existing Vector API. The Vector API struck a balance between cross‑platform portability and low‑level performance, but its design had to omit certain platform‑specific capabilities, making it inadequate for some classes of highly vectorized algorithms. With recent progress in Project Panama — notably the Foreign Function & Memory API and jextract — Ivanov shows a path to expose individual machine instructions from Java in a performant way, evolving from ad‑hoc machine code snippets to JVM intrinsics and now to a principled low‑level API. For the AI/ML community this matters because many high-performance kernels rely on platform-specific primitives (e.g., wide SIMD, matrix‑multiply or fused ops on AVX/SVE) that generic vector APIs can’t express efficiently. A hardware intrinsics API would let Java code call those instructions directly while preserving JVM performance and safety, enable simpler implementations in the Vector API, JDK and JVM, and make Java a more viable target for compute‑intensive ML workloads and specialized kernels. In short, the proposal narrows the gap between Java and bare‑metal performance without abandoning portability, opening new opportunities for optimized inference and training primitives in the Java ecosystem.