Release Notes

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Release Notes#

This section includes the KernelGen release information.

V2.1.0#

  • Added features

    • Added support for the Sunrise AI accelerator platform, expanding the number of supported chips from six to seven.

  • Enhanced features

    • Experimental TLE support has been extended to the Web platform.

V2.0.0#

  • Added features๏ผš

    • Added support for creating, optimizing, and specializing Kernels across multiple hardware platforms via the KernelGen Operator Development MCP Toolkit, AI agents, and first- and third-party skills.

    • Added support for generating the FlagTree TLE operator on NVIDIA hardware platforms. TLE operator generation capability is an experimental feature currently under active development.

    • Extended testing device support to include MetaX platform.

    • Introduced a History panel to track modifications to the Kernel code.

V1.0.0#

  • Added features๏ผš

    • Basic Workflow: Supports single, fixed-step code generation including GroundTruth โ†’ TritonKernel โ†’ Correctness Test โ†’ Performance Test.

    • User Registration: Supports self-service registration and application, with platform approval required for trial use.

    • Web Interface: Online access at https://kernelgen.flagos.io/.

    • Core Features:

      • Fully Automated Workflow: Automatically generates, tests, and optimizes complete AI operator sets.

      • Multi-Backend Support: Seamlessly supports multiple AI libraries and chips with automatic adaptation and debugging.

      • Easy-to-Use: Browser-based interface requiring no setup or prior experience.

      • Standardized Verification: Automatically generates test cases to ensure operator correctness.

      • Deep Ecosystem Integration: Collaborates with FlagGems and FlagTree to accelerate operator library development.

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