April 2026 performance and developer experience sprint for iree-org/wave. Delivered a universal N-dimensional read index linearization pipeline with 1-D memory accesses, extended to dynamic-stride and GatherToLDS paths, improved register efficiency, and added tests validating behavior on shuffled layouts (mxfp4). Reconciled linearization with epilogue elimination to prevent memory faults. Enhanced test coverage across non-contiguous layouts and runtime contiguity checks. Dev experience improvements include a new environment setup script (wave-dev-setup.sh) and standardized uv-based installation guidance to speed onboarding. Implemented Split-K GEMM optimizations for MXFP4, including bf16-precision atomic support, memory-access tiling improvements, and updated scheduling constraints for the new architecture. These changes reduce memory bandwidth pressure, lower register pressure, improve portability, and accelerate developer onboarding and iteration.

March 2026 performance summary for iree-org/wave: Delivered significant kernel and backend enhancements, targeting dynamic shapes, memory safety, and backend correctness. Achieved notable compile-time performance gains, improved correctness under workgroup reordering, enhanced Waveasm translation, and automated ROCm/PyTorch compatibility flows. This period focused on delivering business value through faster builds, more reliable kernels, and streamlined developer tooling across GPU backends.

Performance-focused month for iree-org/wave (Feb 2026). Core work centered on GEMM kernel optimizations and FP16 workflow improvements that directly increase runtime performance and broaden hardware coverage. The work delivered two key feature sets with measurable efficiency gains and fixes that improve correctness for split-k GEMMs.

Month: 2026-01 Key features delivered and bugs fixed across repositories: - iree-org/iree: Floating point type conversion between f32 and f64 in VM lists. Implemented conversion logic and added tests to validate behavior, addressing zero-value issues when types mismatch. Commit 6acc288dcd93e8465291bcf37f82c31504564487. Business value: reliable data marshaling between VM types enhances correctness of runtime pipelines and cross-component interoperability. - iree-org/wave: Persistent GEMM kernel optimization with user tutorial. Implemented a persistent kernel with workgroup reordering and cache reuse (L2 and MALL), plus a comprehensive user tutorial. Commit 196038bfaa3eb438030868f33edc7b58bb3f2d37. Business value: measurable GEMM performance improvements for dense workloads and improved developer guidance through documentation. - iree-org/wave: GetResult injection bug in complex control flow. Fixed handling of GetResult for complex flows involving Placeholders to access results from Iterate or Conditional nodes in nested structures. Commit 1f1a744f95044f3040974843b28e3657e8ae5ecd. Business value: correctness in nested kernels, reducing runtime errors in complex graphs. - iree-org/wave: Dynamic software pipelining for loops with dynamic shapes. Added dynamic software pipelining in a conditional framework with a pipelined loop (prologue/loop/epilogue) and a non-pipelined remainder loop; generalized is_barrier_between; tests added (scheduling_to_mlir.py, test_loop_pipeline.py). Commit 49498b2c6764977911303657391d81ebb11c0190. Business value: improved performance and robustness for dynamic-shape workloads, better resource utilization, and deeper test coverage. Overall impact and accomplishments: - Delivered cross-repo improvements spanning correctness, performance, and developer experience within 2026-01. - Expanded test coverage and documentation to support reliability and onboarding (tutorials, end-to-end tests). - Demonstrated proficiency in low-level systems programming, performance optimization, dynamic scheduling, and test automation. Technologies/skills demonstrated: - Low-level C++/MLIR-inspired runtime and kernel development, dynamic software pipelining, cache-aware optimization, graph/instruction scheduling, and robust test strategies.

Concise monthly summary for 2025-12 focusing on Wave repository work, highlighting deliverables, fixes, impact, and skills demonstrated. Key features and stability improvements drive debugging efficiency, runtime performance, and API consistency across the Wave workflow.

October 2025 milestones centered on enabling efficient tensor top-k operations, stronger GPU debugging and RDNA4 readiness, and robust test infrastructure. Key features delivered include TopKOp for tensors with a reduction-based algorithm and accompanying refactors/tests in wave; enhanced kernel debugging with DISubprogram attributes preserving source locations through MLIR/LLVM, plus RDNA4 compatibility improvements; test harness improvements to align FileCheck across Python and C++ implementations; and a new HIP debug flag to preserve LLVMGPU debug symbols for profiling with Wave. These changes collectively improve performance-critical workloads, enable accurate profiling and debugging, ensure hardware-agnostic reliability, and reduce CI frictions.

September 2025: Focused on advancing location tracking, debugging, and operator versatility in the Wave ecosystem, delivering end-to-end traceability from TorchFX through MLIR and ensuring robust test coverage. Strengthened observability and governance around location data to speed diagnosis and protect correctness in codegen pipelines across the Wave compiler and runtime.

August 2025: Focused on delivering robust debugging tooling and aligning codebase terminology for iree-org/wave. Delivered tangible business value by enhancing debugging efficiency, improving tensor visualization in the HTML viewer, and clarifying kernel semantics for maintainability and future work.

July 2025: Focused on observability, performance configurability, and stability for the Wave project. Key features include the Wave Debugging and Diagnostics Toolkit with dynamic shapes, API rename to debug_log, cache behavior improvements, and end-to-end tests; a new Wave compiler optimization_level flag with cross-configuration tests; and targeted correctness and documentation improvements that reduce risk and improve developer productivity. This combination improves in-kernel observability, configurable optimizations, and overall reliability, delivering business value through faster debugging cycles, more performant builds, and fewer regressions.

June 2025 monthly summary for iree-org/wave: Delivered floating-point exponentiation support (powf) in the Wave kernel, including binary-op registration, type checks, and targeted tests. No major bugs reported this month. This work expands the kernel's math capabilities, enabling powf usage in Wave-based workloads while ensuring correctness and safety through strict type enforcement and tests. The update lowers future integration costs for numeric workloads and improves developer confidence driving numerical features in Wave.