Helion

Helion's auto-tuning system automatically searches for the optimal combination of parameters such as tile size, loop tiling, and memory layout at compile time.

With a general-purpose Helion kernel, adding support for a new quantization format only requires modifying the high-level descriptive logic rather than writing and validating a new low-level kernel from scratch.

This integration work used a general-purpose Linear kernel written in Helion to cover scenarios in the vLLM linear backend that previously required multiple specialized implementations.

Commonwealth Fusion Systems (CFS)'s Brandon Sorbom and Helion's David Kirtley will discuss pathways to fusion commercialization on the Smart Systems stage at TechCrunch Disrupt 2026.

Helion uses a field-reversed configuration (FRC) approach and emphasizes directly converting fusion energy into electricity, attempting to bypass the conventional steam turbine power generation step.

Helion has developed a "colliding compression" approach in which two plasma masses collide at high speed from both ends, heating and compressing them to fusion conditions, and directly inducing a current through changes in the magnetic field.

Private fusion companies such as Commonwealth Fusion, Helion, and TAE Technologies are compressing the commercialization timeline to the 2030s through technical approaches including high-temperature superconducting magnets and novel confinement configurations.

Hugging Face's Kernels project now supports Helion.

Helion automatically searches for the optimal execution configuration through an autotune mechanism, enabling the same operator code to automatically find near-optimal parameter combinations for different GPUs.

Helion is a high-level language/compilation framework for writing GPU operators that describes computational logic in a Python-like syntax, which the compiler then uses to generate low-level high-performance code.