Helion

Helion is developing a new semiconductor technology that is said to be able to double the plant's output power.

Most fusion startups focus their efforts on plasma confinement and sustaining the reaction, whereas Helion also brings power electronics devices into in-house development.

Microsoft's agreement with Helion is one of the first publicly disclosed corporate power purchase commitments in the fusion field, and details of its structure (such as guaranteed output, default clauses, and how the electricity price is linked) have not been fully disclosed.

Helion's first fusion power plant is planned to supply power to Microsoft, with a target date of 2028.

Helion's power supply agreement with Microsoft is one of the few publicly disclosed power purchase commitments in the fusion industry.

According to the PyTorch blog, the integration of Helion and CompileIQ lets the tuner find better configurations in less time, because compiler-level search is incorporated into a unified tuning process.

The actual effect of the Helion and CompileIQ integration still needs to be verified on real workloads.

Helion and CompileIQ combine to form a "one search, two layers of control" architecture: the outer layer uses the Helion autotuner to search kernel-level parameters, while the inner layer has CompileIQ make compiler-level optimization decisions.

Helion's autotuner automatically tries different combinations of parameters such as tile size, parallelization strategy and memory layout.

Helion is still a relatively young project, and the CompileIQ integration is also at an early stage.

The integration of PyTorch Helion and NVIDIA CompileIQ reflects the increasingly close collaboration between deep learning frameworks and hardware vendors' toolchains.

Helion's autotuner can search different configurations to find the best-performing implementation for a kernel.

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.

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.

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.

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.

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.

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.