google/heir
Oct 2024 – Oct 2025
13 Months active
Languages Used
C++MLIRYAMLPythonMarkdownTableGenBUILDLLVM IR
Technical Skills
CI/CDCompiler DevelopmentDevOpsDomain-Specific Languages (DSLs)FHE KernelsHomomorphic Encryption
Asra Ali
PROFILE
Asra Ali
Asraa contributed to the google/heir repository by building advanced compiler infrastructure for privacy-preserving machine learning and cryptographic workloads. She engineered MLIR-based lowering passes, optimized tensor and layout propagation, and implemented arithmetic DAG kernels for linear algebra, enabling efficient translation from high-level operations to secure hardware and cryptographic backends. Her work integrated C++ and Python for IR manipulation, algorithmic optimization, and robust CI/CD pipelines, while expanding support for dialect conversion, layout tooling, and backend emitters in Rust and Verilog. The depth of her contributions is reflected in the breadth of features, rigorous testing, and maintainable code organization across the project.
Overall Statistics
Feature vs Bugs
68%Features
Repository Contributions
145Total
Bugs
33
Commits
145
Features
70
Lines of code
56,646
Activity Months13
Your Network
4212 people
Work History
October 2025
8 Commits • 7 Features
Oct 1, 2025Concise monthly summary for 2025-10 focused on business value delivery and technical achievements across the google/heir repository. The month emphasized enabling native support for common ML workloads, improving compiler/lowering passes, and strengthening layout/pattern optimizations to boost performance and robustness.
8 Commits • 7 Features
Oct 1, 2025Concise monthly summary for 2025-10 focused on business value delivery and technical achievements across the google/heir repository. The month emphasized enabling native support for common ML workloads, improving compiler/lowering passes, and strengthening layout/pattern optimizations to boost performance and robustness.
October 2025
September 2025
15 Commits • 5 Features
Sep 1, 2025September 2025 focused on expanding arithmetic capabilities, improving data path layout handling, and stabilizing infrastructure to accelerate cryptographic linear algebra workloads. Delivered the Halevi-Shoup arithmetic DAG kernel for matmul and matvec with unit tests, enabled 2D convolution via matrix–vector operations with layout propagation, extended the OpenFhePke emitter to translate SCF if/for statements, and advanced scalar and layout propagation in ConvertToCiphertextSemantics. Retained Chebyshev basis form to support efficient evaluation, and completed key maintenance to keep dependencies and tooling up to date.
September 2025
15 Commits • 5 Features
Sep 1, 2025September 2025 focused on expanding arithmetic capabilities, improving data path layout handling, and stabilizing infrastructure to accelerate cryptographic linear algebra workloads. Delivered the Halevi-Shoup arithmetic DAG kernel for matmul and matvec with unit tests, enabled 2D convolution via matrix–vector operations with layout propagation, extended the OpenFhePke emitter to translate SCF if/for statements, and advanced scalar and layout propagation in ConvertToCiphertextSemantics. Retained Chebyshev basis form to support efficient evaluation, and completed key maintenance to keep dependencies and tooling up to date.
August 2025
21 Commits • 13 Features
Aug 1, 2025August 2025 saw a strong focus on advancing tensor layout, rotation/reduction workflows, and privacy-enabled ML backends, while tightening reliability through targeted bug fixes and CI improvements. Delivered new tensor_ext capabilities, row-major layout tooling, and layout attribute handling, enabling more aggressive optimizations and easier downstream integration. Backend readiness for secret-sharing workflows (CKKS/OpenFHE) progressed with reshape support, enhanced tensor extract/collapse handling, and inliner improvements for ML activation functions. Concurrently, critical bugs were resolved to stabilize canonicalizations, shape handling, and error messaging, contributing to a smoother developer experience and more predictable performance.
21 Commits • 13 Features
Aug 1, 2025August 2025 saw a strong focus on advancing tensor layout, rotation/reduction workflows, and privacy-enabled ML backends, while tightening reliability through targeted bug fixes and CI improvements. Delivered new tensor_ext capabilities, row-major layout tooling, and layout attribute handling, enabling more aggressive optimizations and easier downstream integration. Backend readiness for secret-sharing workflows (CKKS/OpenFHE) progressed with reshape support, enhanced tensor extract/collapse handling, and inliner improvements for ML activation functions. Concurrently, critical bugs were resolved to stabilize canonicalizations, shape handling, and error messaging, contributing to a smoother developer experience and more predictable performance.
August 2025
July 2025
14 Commits • 4 Features
Jul 1, 2025July 2025 monthly summary for google/heir focusing on delivering performance improvements, dialect upgrades, build/CI robustness, and code maintenance with observable business value.
July 2025
14 Commits • 4 Features
Jul 1, 2025July 2025 monthly summary for google/heir focusing on delivering performance improvements, dialect upgrades, build/CI robustness, and code maintenance with observable business value.
June 2025
9 Commits • 4 Features
Jun 1, 2025June 2025 monthly summary for google/heir focusing on MLIR/Linalg improvements, front-end enhancements, and test architecture. Key contributions in this period center on delivering performance-oriented optimizations, expanding language/tool support, and improving maintainability of the emitter test suite. Key features delivered: - Linalg canonicalizations and related shape/transpose optimizations: Consolidated Linalg canonicalization patterns and optimizations, including folding constant fills/broadcasts in Linalg, removing unit dimensions in linalg.map, folding away certain broadcasts, and optimizing transposed matvec/vecmat scenarios to boost MLIR/Linalg performance. - FoldConstantTensors pass: Introduced a new FoldConstantTensors pass to fold constant tensor operations (e.g., tensor.insert, tensor.collapse_shape) directly into new constant tensors, simplifying models and MLIR pipelines. - Verilog emitter enhancements: Added support for modulo and division operations in the Verilog emitter frontend, updating translation and tests. - Emitter tests organization: Centralized emitter tests under tests/Emitter to improve maintainability and discoverability. Major bugs fixed: - GenericOp printer parentheses bug: Ensured parentheses are always printed (even for ops without inputs) and added regression tests. - Forward-insert-to-extract traversal bug: Refined traversal of the use-def chain for inserted tensors with getValueAtIndex, improving reliability across tensor ops. Overall impact and accomplishments: - Strengthened MLIR/Linalg tooling with performance-oriented canonicalizations and a more robust constant-tensor folding path, enabling simpler and faster model lowerings. - Expanded frontend capability (Verilog) and improved correctness and reliability of IR printing and tensor pipelines. - Improved maintainability and test quality through reorganized emitter tests. Technologies/skills demonstrated: - MLIR/Linalg canonicalization patterns, shape/transpose optimizations, and folding passes. - Tensor operation folding and constant tensor propagation. - Verilog frontend translation and testing. - IR printer reliability and forward/insertion pass robustness. - Test organization and maintainability practices.
9 Commits • 4 Features
Jun 1, 2025June 2025 monthly summary for google/heir focusing on MLIR/Linalg improvements, front-end enhancements, and test architecture. Key contributions in this period center on delivering performance-oriented optimizations, expanding language/tool support, and improving maintainability of the emitter test suite. Key features delivered: - Linalg canonicalizations and related shape/transpose optimizations: Consolidated Linalg canonicalization patterns and optimizations, including folding constant fills/broadcasts in Linalg, removing unit dimensions in linalg.map, folding away certain broadcasts, and optimizing transposed matvec/vecmat scenarios to boost MLIR/Linalg performance. - FoldConstantTensors pass: Introduced a new FoldConstantTensors pass to fold constant tensor operations (e.g., tensor.insert, tensor.collapse_shape) directly into new constant tensors, simplifying models and MLIR pipelines. - Verilog emitter enhancements: Added support for modulo and division operations in the Verilog emitter frontend, updating translation and tests. - Emitter tests organization: Centralized emitter tests under tests/Emitter to improve maintainability and discoverability. Major bugs fixed: - GenericOp printer parentheses bug: Ensured parentheses are always printed (even for ops without inputs) and added regression tests. - Forward-insert-to-extract traversal bug: Refined traversal of the use-def chain for inserted tensors with getValueAtIndex, improving reliability across tensor ops. Overall impact and accomplishments: - Strengthened MLIR/Linalg tooling with performance-oriented canonicalizations and a more robust constant-tensor folding path, enabling simpler and faster model lowerings. - Expanded frontend capability (Verilog) and improved correctness and reliability of IR printing and tensor pipelines. - Improved maintainability and test quality through reorganized emitter tests. Technologies/skills demonstrated: - MLIR/Linalg canonicalization patterns, shape/transpose optimizations, and folding passes. - Tensor operation folding and constant tensor propagation. - Verilog frontend translation and testing. - IR printer reliability and forward/insertion pass robustness. - Test organization and maintainability practices.
June 2025
May 2025
10 Commits • 5 Features
May 1, 2025May 2025: Implemented CGGI decomposition improvements enabling decomposition of high-level CGGI ops into lower-level LWE and PBS backends, and moved canonicalization of LUT2/LUT3 into the decomposition workflow; fixed secret-to-CGGI lowering. Stabilized dialect conversion by addressing memref-global-replace rollback behavior. Extended Verilog tensor emission and tensor-to-scalars support for multi-dimensional tensors, and added TFHE backend bitwise XOR support with tests. Introduced layout conversion hoisting to function arguments and added a weekly Bazel lockfile update workflow in CI. These changes deliver faster backend integration, more reliable dialect conversions, richer cryptographic/hardware support, and streamlined dependency management.
May 2025
10 Commits • 5 Features
May 1, 2025May 2025: Implemented CGGI decomposition improvements enabling decomposition of high-level CGGI ops into lower-level LWE and PBS backends, and moved canonicalization of LUT2/LUT3 into the decomposition workflow; fixed secret-to-CGGI lowering. Stabilized dialect conversion by addressing memref-global-replace rollback behavior. Extended Verilog tensor emission and tensor-to-scalars support for multi-dimensional tensors, and added TFHE backend bitwise XOR support with tests. Introduced layout conversion hoisting to function arguments and added a weekly Bazel lockfile update workflow in CI. These changes deliver faster backend integration, more reliable dialect conversions, richer cryptographic/hardware support, and streamlined dependency management.
April 2025
24 Commits • 11 Features
Apr 1, 2025Month: 2025-04 — Key features delivered include an end-to-end RLWE-based cmux example to demonstrate practical cryptographic pipelines; UX improvements with CLI/translation flag renames to --mlir-to-cggi and --to-XYZ; Verilog/CGGI enhancements for broader hardware translation capabilities; cross-cutting improvements in Secret-to-CGGI and memref handling; and notable build/platform improvements (Yosys-based build hardening and enabling non-Yosys mlir-to-cggi paths). Major open-source style bug fixes were also completed to increase reliability, including default handling for OpenFHE params, build fixes for Yosys, indexing safety in Verilog, test stability, and TFHE server-key warning behavior. In addition, macOS frontend tooling gains (Pybind11 libraries) and TFHE/OpenFHE emitter/frontend enhancements contributed to broader platform coverage and performance readiness.
24 Commits • 11 Features
Apr 1, 2025Month: 2025-04 — Key features delivered include an end-to-end RLWE-based cmux example to demonstrate practical cryptographic pipelines; UX improvements with CLI/translation flag renames to --mlir-to-cggi and --to-XYZ; Verilog/CGGI enhancements for broader hardware translation capabilities; cross-cutting improvements in Secret-to-CGGI and memref handling; and notable build/platform improvements (Yosys-based build hardening and enabling non-Yosys mlir-to-cggi paths). Major open-source style bug fixes were also completed to increase reliability, including default handling for OpenFHE params, build fixes for Yosys, indexing safety in Verilog, test stability, and TFHE server-key warning behavior. In addition, macOS frontend tooling gains (Pybind11 libraries) and TFHE/OpenFHE emitter/frontend enhancements contributed to broader platform coverage and performance readiness.
April 2025
March 2025
11 Commits • 6 Features
Mar 1, 2025March 2025: Delivered key feature enhancements in MLIR/OpenFHE emitters, expanded testing and CI reliability, and modernized dependencies. The work enables more flexible loop handling, richer typing, and serialization of cryptographic elements, improving performance, reliability, and deployment readiness across cryptographic and MLIR-backed pipelines.
March 2025
11 Commits • 6 Features
Mar 1, 2025March 2025: Delivered key feature enhancements in MLIR/OpenFHE emitters, expanded testing and CI reliability, and modernized dependencies. The work enables more flexible loop handling, richer typing, and serialization of cryptographic elements, improving performance, reliability, and deployment readiness across cryptographic and MLIR-backed pipelines.
February 2025
12 Commits • 3 Features
Feb 1, 2025February 2025 — google/heir monthly summary focused on strengthening test coverage, cryptographic translation workflows, and build stability to reduce risk and improve deployment confidence for privacy-preserving ML workloads.
12 Commits • 3 Features
Feb 1, 2025February 2025 — google/heir monthly summary focused on strengthening test coverage, cryptographic translation workflows, and build stability to reduce risk and improve deployment confidence for privacy-preserving ML workloads.
February 2025
January 2025
8 Commits • 5 Features
Jan 1, 2025Monthly summary for 2025-01 focused on delivering core infrastructure, feature expansions, and reliability improvements for google/heir. Key features delivered include CI and testing infrastructure improvements, Python frontend loop support with MLIR emission, OpenFHE SubPlainOp, Squat Packing for secret-tensor matmul, and AddClientInterface refinement. Major bugs fixed include CI-related failures (test CI without cache hit) and TOSA test failures after upstream changes, with accompanying test adjustments to keep CI green. Overall impact: improved CI reliability and feedback loop, extended language and IR capabilities, and more efficient secure computation workflows, enabling faster delivery of cryptographic and ML workloads. Technologies demonstrated: Bazel/CI caching, pre-commit hooks; MLIR and Python frontend; OpenFHE dialect and emitter; Squat Packing algorithm; interface generation heuristics; comprehensive tests.
January 2025
8 Commits • 5 Features
Jan 1, 2025Monthly summary for 2025-01 focused on delivering core infrastructure, feature expansions, and reliability improvements for google/heir. Key features delivered include CI and testing infrastructure improvements, Python frontend loop support with MLIR emission, OpenFHE SubPlainOp, Squat Packing for secret-tensor matmul, and AddClientInterface refinement. Major bugs fixed include CI-related failures (test CI without cache hit) and TOSA test failures after upstream changes, with accompanying test adjustments to keep CI green. Overall impact: improved CI reliability and feedback loop, extended language and IR capabilities, and more efficient secure computation workflows, enabling faster delivery of cryptographic and ML workloads. Technologies demonstrated: Bazel/CI caching, pre-commit hooks; MLIR and Python frontend; OpenFHE dialect and emitter; Squat Packing algorithm; interface generation heuristics; comprehensive tests.
December 2024
5 Commits • 2 Features
Dec 1, 2024December 2024 monthly summary for google/heir: Delivered governance/documentation enhancements, corrected cryptographic LUT processing, and expanded the CGGI IR/tooling stack. This work improves stakeholder visibility, correctness, and development velocity by establishing a formal documentation baseline, fixes to LUT2/LUT3 canonicalization, and robust tooling/IR infrastructure to support future CGGI optimizations.
5 Commits • 2 Features
Dec 1, 2024December 2024 monthly summary for google/heir: Delivered governance/documentation enhancements, corrected cryptographic LUT processing, and expanded the CGGI IR/tooling stack. This work improves stakeholder visibility, correctness, and development velocity by establishing a formal documentation baseline, fixes to LUT2/LUT3 canonicalization, and robust tooling/IR infrastructure to support future CGGI optimizations.
December 2024
November 2024
5 Commits • 3 Features
Nov 1, 2024November 2024 (google/heir) focused on reliability, modularity, and developer experience. Key features delivered include enhancements to the LWE dialect and a major refactor of pipeline registrations, while patching critical bugs that impacted notebook usability and polynomial lowering stability. Developer tooling improvements were implemented to harden the commit workflow and code quality checks. The combined work improved observable behavior in Jupyter environments, strengthened the cryptographic type model, and reduced maintenance overhead by clarifying responsibilities across pipeline code paths.
November 2024
5 Commits • 3 Features
Nov 1, 2024November 2024 (google/heir) focused on reliability, modularity, and developer experience. Key features delivered include enhancements to the LWE dialect and a major refactor of pipeline registrations, while patching critical bugs that impacted notebook usability and polynomial lowering stability. Developer tooling improvements were implemented to harden the commit workflow and code quality checks. The combined work improved observable behavior in Jupyter environments, strengthened the cryptographic type model, and reduced maintenance overhead by clarifying responsibilities across pipeline code paths.
October 2024
3 Commits • 2 Features
Oct 1, 2024October 2024 (google/heir) delivered notable end-to-end enhancements in homomorphic encryption workflows, CI reliability, and encryption-key capabilities. The work enabled faster experimentation and more robust production use by integrating Linalg FHE kernels into the MLIR-to-OpenFHE CKKS pipeline with benchmarking, stabilizing CI for dependency management, and expanding key options with packed server keys.
3 Commits • 2 Features
Oct 1, 2024October 2024 (google/heir) delivered notable end-to-end enhancements in homomorphic encryption workflows, CI reliability, and encryption-key capabilities. The work enabled faster experimentation and more robust production use by integrating Linalg FHE kernels into the MLIR-to-OpenFHE CKKS pipeline with benchmarking, stabilizing CI for dependency management, and expanding key options with packed server keys.
October 2024
Activity
Loading activity data...
Quality Metrics
Correctness89.0%
Maintainability86.6%
Architecture87.4%
Performance79.4%
AI Usage20.6%
Skills & Technologies
Programming Languages
BUILDBashBazelBzlCC++CMakeLLVM IRMLIRMarkdown
Technical Skills
AES CryptographyAbstract InterpretationAlgorithm DesignAlgorithm ImplementationAlgorithm implementationArithmetic DAGsArithmetic OperationsAttribute HandlingBazelBazel Build SystemBuild SystemBuild System ConfigurationBuild System ManagementBuild SystemsC++
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline