
Lazar Djurovic developed and optimized low-level kernel and testing infrastructure across the tenstorrent/tt-llk and tt-metal repositories, focusing on performance-critical paths such as Scaled Dot-Product Attention and matrix operations. He enhanced test automation and reliability by expanding multi-tile and AI-generated test coverage, refactoring C++ and Python code, and integrating hardware-accelerated validation for embedded systems. His work included debugging and optimizing kernel algorithms, implementing performance profiling, and improving test fidelity for floating-point and integer operations. By addressing both feature development and bug fixes, Lazar delivered robust, maintainable code that accelerated validation cycles and enabled data-driven optimization for hardware-software integration.

October 2025: Focused on performance optimization in the SDPA path for tenstorrent/tt-llk. Implemented unpacker and kernel enhancements to enable element-wise subtraction between column tiles and tiled data, accelerating Scaled Dot-Product Attention. Added comprehensive tests and configuration options to validate the optimized path. The change is captured in commit 4de2e5b0b5b03da1297b5473b8ecb0ac94f92138.
October 2025: Focused on performance optimization in the SDPA path for tenstorrent/tt-llk. Implemented unpacker and kernel enhancements to enable element-wise subtraction between column tiles and tiled data, accelerating Scaled Dot-Product Attention. Added comprehensive tests and configuration options to validate the optimized path. The change is captured in commit 4de2e5b0b5b03da1297b5473b8ecb0ac94f92138.
September 2025: Focused on strengthening test infrastructure and performance visibility for the SDPA path in tt-metal. Delivered enhanced testing framework, introduced performance profiling capabilities, and validated multi-core test execution, enabling data-driven optimizations and faster QA cycles.
September 2025: Focused on strengthening test infrastructure and performance visibility for the SDPA path in tt-metal. Delivered enhanced testing framework, introduced performance profiling capabilities, and validated multi-core test execution, enabling data-driven optimizations and faster QA cycles.
August 2025 performance highlights across tt-llk and tt-metal, focusing on expanded test coverage, kernel optimization, and reliability improvements that drive faster validation and better performance characteristics for fused operations and attention kernels.
August 2025 performance highlights across tt-llk and tt-metal, focusing on expanded test coverage, kernel optimization, and reliability improvements that drive faster validation and better performance characteristics for fused operations and attention kernels.
July 2025 performance and reliability month focused on expanding kernel capabilities, improving test fidelity, and delivering measurable performance gains across tt-llk and tt-metal. Key accomplishments include expanding multi-tile support for core operations in tt-llk (unpack untilize, SFPU tests, and matmul) to handle multi-tile inputs for square tensors; introducing ttnn.where for LLK with SFPU kernels and associated API cleanup and iteration handling; implementing fidelity masking in test infrastructure to enhance accuracy of golden data for element-wise operations and matmul; and a performance optimization in tt-metal via a shift-and-add multiplication algorithm for int32 to reduce operation count and improve throughput.
July 2025 performance and reliability month focused on expanding kernel capabilities, improving test fidelity, and delivering measurable performance gains across tt-llk and tt-metal. Key accomplishments include expanding multi-tile support for core operations in tt-llk (unpack untilize, SFPU tests, and matmul) to handle multi-tile inputs for square tensors; introducing ttnn.where for LLK with SFPU kernels and associated API cleanup and iteration handling; implementing fidelity masking in test infrastructure to enhance accuracy of golden data for element-wise operations and matmul; and a performance optimization in tt-metal via a shift-and-add multiplication algorithm for int32 to reduce operation count and improve throughput.
June 2025: Major upgrade to the SFPU testing framework in tenstorrent/tt-llk, delivering tile-level and multi-tile test capabilities and binary test execution, along with improved utilities (parameterization, address generation, tile-count handling). Fixed targeted reliability issues in fidelity-based test selection and SFPI v_if path to reduce flaky failures and ensure correct operation paths. This work expands hardware validation coverage, accelerates feedback, and demonstrates proficiency in test automation, hardware-software integration, and CI readiness.
June 2025: Major upgrade to the SFPU testing framework in tenstorrent/tt-llk, delivering tile-level and multi-tile test capabilities and binary test execution, along with improved utilities (parameterization, address generation, tile-count handling). Fixed targeted reliability issues in fidelity-based test selection and SFPI v_if path to reduce flaky failures and ensure correct operation paths. This work expands hardware validation coverage, accelerates feedback, and demonstrates proficiency in test automation, hardware-software integration, and CI readiness.
May 2025 monthly summary for tenstorrent/tt-llk: Focused on strengthening test reliability and coverage through targeted test-suite improvements and a stability fix for cosine tests. Key progress: reduced flaky failures, improved parametrization, and clearer test instrumentation; enabling faster feedback and safer releases.
May 2025 monthly summary for tenstorrent/tt-llk: Focused on strengthening test reliability and coverage through targeted test-suite improvements and a stability fix for cosine tests. Key progress: reduced flaky failures, improved parametrization, and clearer test instrumentation; enabling faster feedback and safer releases.
April 2025 monthly summary for tenstorrent/tt-llk. Delivered a focused matmul test correctness fix and test harness cleanup, improving reliability and establishing a solid base for matrix operation validation. The changes corrected the element read order in unpack.py, updated the C++ test template arguments, and implemented a standard 3-loop matrix multiplication with input matrices stored in L1. Enabled testing with two random tiles in Float16_b format, and performed Packer code cleanup as part of the fix. These improvements reduce flaky tests, lower CI risk, and accelerate future matmul validation and integration work.
April 2025 monthly summary for tenstorrent/tt-llk. Delivered a focused matmul test correctness fix and test harness cleanup, improving reliability and establishing a solid base for matrix operation validation. The changes corrected the element read order in unpack.py, updated the C++ test template arguments, and implemented a standard 3-loop matrix multiplication with input matrices stored in L1. Enabled testing with two random tiles in Float16_b format, and performed Packer code cleanup as part of the fix. These improvements reduce flaky tests, lower CI risk, and accelerate future matmul validation and integration work.
March 2025 monthly summary for tenstorrent/tt-llk: Stabilized utilization instrumentation across architectures by fixing unpack_tilize for the Blackhole (BH) architecture, addressing a regression that caused test failures. The patch ensures unpack_tilize tests pass on both Whitehole (WH) and BH, and enables test_tilize_calculate_untilize to pass, reducing flaky tests and improving reliability of utilization metrics used for performance evaluation and capacity planning. Impact: Higher confidence in cross-arch performance data, reduced flaky test behavior, and improved foundation for optimization cycles across BH and WH deployments.
March 2025 monthly summary for tenstorrent/tt-llk: Stabilized utilization instrumentation across architectures by fixing unpack_tilize for the Blackhole (BH) architecture, addressing a regression that caused test failures. The patch ensures unpack_tilize tests pass on both Whitehole (WH) and BH, and enables test_tilize_calculate_untilize to pass, reducing flaky tests and improving reliability of utilization metrics used for performance evaluation and capacity planning. Impact: Higher confidence in cross-arch performance data, reduced flaky test behavior, and improved foundation for optimization cycles across BH and WH deployments.
February 2025: Focused on establishing a robust testing foundation for LLK and TenSIX firmware groundwork. No major defects fixed this month; work concentrated on infrastructure, cross-format and cross-architecture test readiness, and laying groundwork for TenSIX RISC-V firmware validation.
February 2025: Focused on establishing a robust testing foundation for LLK and TenSIX firmware groundwork. No major defects fixed this month; work concentrated on infrastructure, cross-format and cross-architecture test readiness, and laying groundwork for TenSIX RISC-V firmware validation.
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