modular/modular
Oct 2025 – Oct 2025
1 Month active
Languages Used
Mojo
Technical Skills
CUDACompiler DevelopmentGPU ProgrammingHigh-Performance ComputingKernel DevelopmentLinear Algebra
Mehdi Goli
PROFILE
Mehdi Goli
During October 2025, Mihir Goli contributed to the modular/modular repository by developing fast exponential approximations for exp2 and exp functions in the standard math library, leveraging Mojo and CUDA with both scalar and SIMD implementations validated through GPU tests. He also engineered a LoRA-oriented kernel for grouped QKV permutation, optimizing storage reuse and output layout for high-performance computing and machine learning workloads. Additionally, Mihir addressed denormalized floating-point handling for NVPTX targets on sm_90+ architectures, ensuring correct sign preservation for subnormals in f16 and f32 formats. His work demonstrated depth in kernel development, numerical methods, and low-level optimization.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
3Total
Bugs
1
Commits
3
Features
2
Lines of code
800
Activity Months1
Your Network
82 people
Work History
October 2025
3 Commits • 2 Features
Oct 1, 20252025-10 monthly summary focused on performance and reliability: Implemented fast exponential approximations in stdlib (exp2/exp) using a cubic FA-4 Horner polynomial with scalar and SIMD paths and GPU tests; added a LoRA-oriented kernel for grouped QKV permutation (lora_shrink_qkv_permute_3mn_sm100) featuring storage reuse and an epilogue for planar outputs, plus comprehensive tests and documentation; fixed NVPTX denormalized FP handling for sm_90+ with sign preservation for f16/f32 and updated PTX tests for optional ftz modifiers. These efforts deliver faster math operations, robust GPU compatibility, and ML-oriented kernel support, driving performance gains in numerical workloads and overall platform reliability.
3 Commits • 2 Features
Oct 1, 20252025-10 monthly summary focused on performance and reliability: Implemented fast exponential approximations in stdlib (exp2/exp) using a cubic FA-4 Horner polynomial with scalar and SIMD paths and GPU tests; added a LoRA-oriented kernel for grouped QKV permutation (lora_shrink_qkv_permute_3mn_sm100) featuring storage reuse and an epilogue for planar outputs, plus comprehensive tests and documentation; fixed NVPTX denormalized FP handling for sm_90+ with sign preservation for f16/f32 and updated PTX tests for optional ftz modifiers. These efforts deliver faster math operations, robust GPU compatibility, and ML-oriented kernel support, driving performance gains in numerical workloads and overall platform reliability.
October 2025
Activity
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Quality Metrics
Correctness96.6%
Maintainability93.4%
Architecture96.6%
Performance100.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Mojo
Technical Skills
CUDACompiler DevelopmentGPU ProgrammingHigh-Performance ComputingKernel DevelopmentLinear AlgebraLow-Level OptimizationMath LibrariesNumerical MethodsPerformance OptimizationSIMD Programming
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