
Vedant Paranjape enhanced floating-point optimization and tensor layout functionality across llvm/llvm-project and google/heir. In llvm/llvm-project, Vedant implemented targeted instruction combining for FAdd and FSub, enabling folding of floating-point additions and subtractions when used with fabs, while ensuring sign-bit correctness through careful code reversion and validation. For google/heir, Vedant expanded TensorExt.Layout to support arbitrary permutation mappings, robust error handling, and validation for NxType inputs and DenseIntElementsAttr, improving layout-driven tensor operations. Working primarily in C++, LLVM IR, and MLIR, Vedant demonstrated depth in compiler optimization and tensor manipulation, delivering maintainable, correctness-focused improvements to both repositories.
February 2026 – Focused on delivering robust layout permutation capabilities in TensorExt.Layout for google/heir, with enhanced validation and broader input support. Key outcomes include arbitrary permutation mapping, improved error handling, and expanded type support (NxType inputs) with robust index validation and DenseIntElementsAttr verification. Commit-level traceability is preserved for auditability and maintainability, enabling safer, more flexible layout-driven optimizations.
February 2026 – Focused on delivering robust layout permutation capabilities in TensorExt.Layout for google/heir, with enhanced validation and broader input support. Key outcomes include arbitrary permutation mapping, improved error handling, and expanded type support (NxType inputs) with robust index validation and DenseIntElementsAttr verification. Commit-level traceability is preserved for auditability and maintainability, enabling safer, more flexible layout-driven optimizations.
September 2025 performance summary: Focused FP optimization and correctness work across LLVM-based projects, with notable gains in folding opportunities and sign-bit correctness. In llvm/llvm-project, delivered a targeted FP instruction combining improvement: FAdd simplifications when the sign bit can be ignored, enabling folding of fadd x, 0 into x when the output feeds into fabs via fabs normalization, and extended this approach to FSub. Commit 092de9bb90cbcee445b31e504a4c2a09ecf09714 documents this work and rationale. In ROCm/llvm-project, reverted an incorrect FSub optimization in InstCombine, removing the optimization and its test to preserve sign-bit semantics (FSub with zero canonicalizes to FAdd with negative zero). Commit c45aa5c764ffcd1f0a4ce9f006f266d664ea6f19 (see #158315). Overall, the month delivered stronger FP folding opportunities with rigorous correctness safeguards, improving generated code quality and reducing sign-bit edge-case risk across platforms.
September 2025 performance summary: Focused FP optimization and correctness work across LLVM-based projects, with notable gains in folding opportunities and sign-bit correctness. In llvm/llvm-project, delivered a targeted FP instruction combining improvement: FAdd simplifications when the sign bit can be ignored, enabling folding of fadd x, 0 into x when the output feeds into fabs via fabs normalization, and extended this approach to FSub. Commit 092de9bb90cbcee445b31e504a4c2a09ecf09714 documents this work and rationale. In ROCm/llvm-project, reverted an incorrect FSub optimization in InstCombine, removing the optimization and its test to preserve sign-bit semantics (FSub with zero canonicalizes to FAdd with negative zero). Commit c45aa5c764ffcd1f0a4ce9f006f266d664ea6f19 (see #158315). Overall, the month delivered stronger FP folding opportunities with rigorous correctness safeguards, improving generated code quality and reducing sign-bit edge-case risk across platforms.

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