[RFC]: add support for Float16Array

[dhruvilmehta]

Full name

Dhruvil Mehta

University status

Yes

University name

California State University, Fullerton

University program

Computer Science

Expected graduation

Summer 2025

Short biography

I am pursuing my Master’s in Computer Science at California State University, Fullerton, where I am developing a version control system for videos to enhance collaboration between video editors and content owners, streamlining version management and ensuring seamless workflows.

I am also a Teaching Associate for CPSC 253: Cybersecurity Foundations and Principles, teaching a class of 40 students for Spring 2025 while deepening my understanding of cybersecurity best practices.

In addition to my studies, I actively contribute to open-source projects using TypeScript and JavaScript. At Code100x: CMS, I earned $200 in bounties for contributions like a certificate download feature, video rendering optimizations, and an in-house course purchase system. As a member of EddieHubCommunity: BioDrop, I contributed to event visualization and bug fixes.

I also have significant experience with C++ in computer graphics, working with OpenGL to create shapes, surfaces, and implement techniques like ray casting and ray tracing, which has strengthened my understanding of graphics algorithms and performance-critical applications.

With diverse technical skills and a passion for impactful projects, I’m always excited to tackle new challenges and continue learning.

Timezone

US Pacific Time (PDT)

Contact details

Email: dhruvilmehta2606@gmail.com, github: dhruvilmehta, LinkedIn: https://www.linkedin.com/in/dhruvil-mehta-1348651b6/

Platform

Linux

Editor

VS Code is my preferred editor because of autocompletion, auto imports, Quick Fixes, and, most importantly, its extensions feature, which allows developers to add powerful functionalities and customize their workflow efficiently.

Programming experience

Here are the links to my projects

1. A version control for videos[Github] (Python)
2. A 16-bit stack-based virtual machine [Github] (Javascript/Typescript)
3. A Pascal Compiler(JVM bytecode) and Interpreter[Github] (Java)
4. Remote Code Execution server (Just like replit)[Github] (Javascript, Kubernetes, Docker, Nginx, Aws)
5. Real-Time Stock Exchange System for faster trade processing[Github] (JavaScript, Redis Queues, TimescaleDb)

JavaScript experience

I have good experience with JavaScript, both in front-end and back-end development, working with frameworks like React and Node.js. My work includes building scalable web applications, optimizing server-side functionality, and contributing to open-source projects.

Open Source Contributions
I actively contribute to open-source projects, mainly using JavaScript and TypeScript:

1. Code100x: [CMS] – Implemented key features for 25,000+ users, including a certificate download system, course purchase system, and video player optimizations, earning $200 in bounties.

2. EddieHubCommunity: [BioDrop] – Developed an event visualization feature and resolved a search functionality bug to enhance user experience.

3. stdlib – Contributed to adding native C and JavaScript support for rempio2f and implemented accessor protocols for various functions.

Most favorite feature
JavaScript’s event loop and non-blocking I/O model make it highly efficient for handling concurrent tasks, especially in server-side applications with Node.js.

Least Favorite Feature
JavaScript’s loose typing can be problematic, allowing unexpected runtime errors. While this provides flexibility, it can lead to debugging challenges in large applications. To mitigate this, I often use TypeScript for better type safety and maintainability.

Node.js experience

I have used NodeJs to build scalable backend services, real-time applications, and microservices. I have worked with frameworks like Express.js, integrating databases such as PostgreSQL, TimescaleDB, and Redis. My projects include developing event-driven architectures using KafkaJS, implementing web sockets for live collaboration, and optimizing API performance. Additionally, I have contributed to open-source projects, enhancing features and fixing critical issues in Node.js based applications.

C/Fortran experience

I have experience with C and C++, mainly in computer graphics. Using OpenGL with C++, I have implemented ray casting, ray tracing, and shape manipulation, deepening my understanding of rendering techniques. Additionally, I contributed to stdlib, adding native C and JavaScript support for rempio2f and implementing accessor protocols for various functions.

Interest in stdlib

I'm interested in stdlib because it brings efficient numerical computing to JavaScript with C under the hood, making operations much faster. I’ve used it for tasks like matrix operations and random number generation in data processing. Its performance and ease of use make it a great tool for handling computational tasks efficiently.

Version control

Yes

Contributions to stdlib

Merged Work
[PR] stdlib-js/stdlib#5908: feat: added accessor protocol to meanpn

Open Work
[PR] stdlib-js/stdlib#6126: feat: add new C implementation for rempio2f
[PR] stdlib-js/stdlib#5914: feat: added accessor protocol to range-by

stdlib showcase

Link: https://dhruvilmehta.github.io/stdlib-showcase/

Goals

1. Implement Float16Array Polyfill

   • Develop a polyfill for Float16Array to replicate its behavior in JavaScript, ensuring support for all common methods and properties (e.g., set, slice, subarray, etc.).
   • Integrate the polyfill into the stdlib codebase, making it available for use in lower versions of JavaScript environments where native support isn't available.

2. C Implementations of operations on float16 values like addition, multiplication and other similar functions

   • Implement Float16 support in C, ensuring seamless integration with stdlib’s native C addons, particularly in the ndarray/* and, number/* namespaces.

3. Backward Compatibility

   • Ensure that the introduction of Float16Array does not break existing functionality. Update relevant parts of the codebase to maintain backward compatibility with older versions of stdlib.

4. Enhance Integration Across Namespaces

   • Extend Float16Array support across various stdlib namespaces, including array/, strided/, and ndarray/*, to make it fully integrated into the project.
   • Ensure that Float16Array is handled similarly to other typed arrays within the project for consistency.

5. Improve Documentation and Tests

   • Write comprehensive tests to ensure Float16Array behaves as expected and meets IEEE 754 compliance standards.
   • Update stdlib documentation to reflect the new support for Float16Array, ensuring users understand how to use the new functionality effectively.

6. Optimize and Refactor the Codebase

   • Refactor and optimize existing code related to typed arrays to better accommodate Float16Array.
   • Identify and address any bugs related to existing typed array operations during integration.

7. Performance Benchmarks

   • Conduct performance benchmarks to assess the efficiency of Float16Array in both JavaScript and C, comparing it with other floating-point types (e.g., Float32Array).
   • Work to minimize memory usage and optimize performance, especially in memory-sensitive applications like scientific computing and data processing.

By focusing on these goals, the project will enable stdlib to handle low-precision floating-point data better and provide a more robust set of tools for users working with memory-sensitive applications.

Why this project?

Adding Float16Array support significantly enhances stdlib’s utility for memory-efficient computing, a crucial aspect of scientific and data-driven applications. This project excites me because it seamlessly blends JavaScript and C, enabling me to leverage my low-level systems expertise while contributing meaningfully through coding, testing, and documentation.

I am excited about the challenge of implementing a Float16Array polyfill, ensuring backward compatibility, and extending support across multiple stdlib namespaces. It would be exciting to work on optimizing performance-critical solutions and improving efficiency in numerical computing. Additionally, the opportunity to engage with the broader open-source community—by refining documentation, writing comprehensive tests, and addressing bugs—adds to the excitement, ensuring that this feature is not only robust but also accessible to developers worldwide.

Qualifications

I am well-qualified to execute this proposal due to my prior experience working with the stdlib repository. Having contributed to the project before, I have developed a strong understanding of its code structure and workflow, enabling me to integrate Float16Array efficiently while maintaining consistency with the existing codebase.

Additionally, I have hands-on experience building low-level systems, including a 16-bit virtual machine in JavaScript. In that project, I used ArrayBuffers to design the memory layout, which strengthened my expertise in handling low-precision data types. This experience directly applies to implementing Float16Array, as I have already tackled the complexities of managing 16-bit values and memory structures. My previous work on this project (https://github.com/dhruvilmehta/16-Bit-Virtual-Machine) demonstrates my ability to handle low-level memory management and data processing tasks effectively.

Prior art

Different libraries, including TensorFlow.js and NumPy, already support the work with half-precision floating point values through float16 (https://groups.google.com/g/cython-users/c/a_gRQJzauJ4). Float16 processing takes priority in machine learning and scientific data applications because libraries integrate their proprietary implementations to work with this data format. WebGL leverages 16-bit float formats through its shaders and rendering duties which demonstrates yet another implementation situation for dealing with float16 precision.

In this stdlib repository, developers have already worked on implementing different typed arrays, including array/bool and array/complex128, which need to connect smoothly with existing codebase structures. Previous typed array implementations serve as valuable references for developing Float16Array while ensuring backward compatibility throughout various library namespaces. The MDN Web Docs and JavaScript-focused resources publish blog posts that demonstrate the specification proposal along with its examples to guide the polyfill while it is being developed.

Commitment

I am fully committed to this project and plan to dedicate 40+ hours per week to it during the Google Summer of Code program. Since it is my summer vacation after the spring semester, I have no exams or other significant commitments during the summer, allowing me to focus entirely on the project. I will ensure consistent and steady progress with well-structured pull requests, comprehensive testing, and regular documentation updates.

Schedule

Assuming a 12 week schedule,

• Community Bonding Period: I will schedule a meeting with the mentors to further develop and concretize the plan which I have proposed.

• Week 1-2: Initial Setup & Constructor Implementation

  • Set up the development environment and finalize the polyfill approach
  • Implement the Float16Array constructor using ArrayBuffer.
    • new Float16Array(), new Float16Array(length), new Float16Array(typedArray), new Float16Array(object
    • Implement the following constructor signatures
      • new Float16Array(buffer), new Float16Array(buffer, byteOffset), new Float16Array(buffer, byteOffset, length
  • Implement basic methods
    • get(index), set(index, value), buffer, byteOffset, byteLength
  • Write initial unit tests for the basic functionality.

• Week 3-4: Core Array Methods Implementation

  • Implement the following array methods
  • from(), of(), at(), copyWithin(), entries(), every(), fill(), filter(), find(), findIndex(), findLast(), findLastIndex(), forEach(), includes()
  • Ensure the polyfill mimics the behavior of Float32Array methods and is compliant with standard typed array operations
  • Continue writing tests for IEEE 754 compliance

• Week 5-6: Core Array Methods Continued & Performance Optimizations

  • Continue implementing the remaining array methods
    • indexOf(), join(), keys(), lastIndexOf(), map(), reduce(), reduceRight(), reverse(), set(), slice(), some(), sort(), subarray(), toLocaleString(), toReversed(), toSorted(), toString(), values(), with().
  • Optimize the implementation to ensure the performance of methods on large arrays.
  • Improve memory efficiency by refining bitwise operations for Float16 precision.
  • Benchmark the performance of Float16Array and compare it with native Float32Array.

• Week 7-8: stdlib Integration

  • Integrate Float16Array across stdlib namespaces (array/, strided/, ndarray).
  • Ensure backward compatibility with existing typed array functions.
  • Add thorough error handling and validation.
  • Document function usage with examples.
  • Conduct further testing and debugging across integration points.

• Week 9-10: Testing & Debugging

  • Expand test coverage by handling edge cases (e.g., negative indices, large arrays).
  • Verify compliance with official TypedArray behavior.
  • Cross-check results with existing JavaScript implementations (if any).
  • Address any bugs or inconsistencies.

• Week 11: Documentation & Final Review

  • Improve documentation, including API references and usage guides
  • Add example use cases in scientific computing and data applications
  • Prepare blog posts/tutorials explaining Float16Array's importance and usage

• Week 12: Final Submission & Wrap-Up

  • Conduct final code cleanup and optimizations
  • Submit the final polyfill implementation and documentation
  • Address last-minute feedback from maintainers
  • Discuss a potential post-GSoC roadmap for further improvements

• Final Week: Wrap up any work and create issues for the necessary upcoming potential ideas and features to add.

Related issues

Issue/Idea: #94
Related Work (which I referred to): https://github.com/stdlib-js/stdlib/wiki/GSoC-2024-%E2%80%90-Jaysukh-Makvana

Checklist

• I have read and understood the Code of Conduct.
• I have read and understood the application materials found in this repository.
• I understand that plagiarism will not be tolerated, and I have authored this application in my own words.
• I have read and understood the patch requirement which is necessary for my application to be considered for acceptance.
• I have read and understood the stdlib showcase requirement which is necessary for my application to be considered for acceptance.
• The issue name begins with [RFC]: and succinctly describes your proposal.
• I understand that, in order to apply to be a GSoC contributor, I must submit my final application to https://summerofcode.withgoogle.com/ before the submission deadline.

[kgryte]

@dhruvilmehta Thanks for opening this RFC. A few questions/comments:

1. What is your strategy for implementing float16 in C? Are you planning on defining a custom type? And how will you smooth over differences among compilers given inconsistent compiler support for built-in half-precision?
2. To support float32 arithmetic operations, ECMAScript added a couple of specialized functions in Math. Will we need to implement any similar functions for float16?
3. To fully support ComplexXXArray in stdlib, we needed to also support @stdlib/complex/* which provided classes for instantiating complex number instances and various utilities for operating on complex numbers. Will we need to do something similar for float16?
4. Can you identify any potential challenges that may need to be addressed when adding Float16Array support?
5. Will we need to add any packages to @stdlib/number/* for supporting half-precision floats?
6. Have you given any thought to math/base/special/* and whether we'll need half-precision implementations there? Or should operations always be performed in, e.g., single-precision? What do other libraries do?

[dhruvilmehta]

1. To implement Float16Array, I'll use ArrayBuffers to manage memory, similar to Float32Array and Float64Array in ECMAScript. This approach will eliminate the need for custom C types. For necessary conversions or low-level operations (e.g., float64ToFloat16), I'll implement helper functions. C implementations may be used if high-performance tasks arise.

2. Some of the functions that would be required are float64tofloat16, float32tofloat16, add, sub, mul, div, etc. I am stating these by referring to the existing numbers/float64 and numbers/float32 packages.

3. As of now, I don't think there is any need for anything like this.

4. When implementing Float16Array, several challenges need to be addressed:

• Conversion between Types:

  • Like how float64ToFloat32 converters exist in the standard library, we would need to implement a float64ToFloat16 converter to handle the precision loss when downcasting from float64 (which is the default number type in JavaScript) to float16.

• Indexing, Slicing, and Memory Management:

  • every read operation must convert the raw 16-bit binary value into a usable Float32 or Float64 value since javascript only supports Float32 and Float64 values.
  • every write operation must convert a Float32/Float64 value into a Float16 representation before storing it.

• Rounding Modes:

  • Implementing proper rounding modes (e.g., rounding to nearest, truncating, etc.) will be essential. The float16 format has fewer bits for the mantissa and exponent, so rounding errors need to be handled carefully to avoid undesired behavior.

5. Yes, we will likely need to add new packages or extend existing ones under @stdlib/number/* to support operations like addition, division, multiplication, and others specifically for Float16Array. We can follow the pattern of the float32 and float64 implementations, which already have helper functions for operations on those types.

6. In general, operations should be performed in float32 to ensure numerical stability and precision. Libraries like NumPy handle float16 values by upcasting them to float32 for most operations. You can refer to https://groups.google.com/g/cython-users/c/a_gRQJzauJ4/m/bIPdVEGDfxAJ and can see functions like npy_half_to_float, npy_half_to_double, npy_float_to_half, npy_double_to_half. The idea is to prevent precision loss by converting float16 to float32 before performing calculations(https://stackoverflow.com/questions/38975770/python-numpy-float16-datatype-operations-and-float8). After the operation, we can convert the result back to float16 if necessary for storage or transmission.

[kgryte]

This approach eliminates the need for custom C types. For necessary conversions or low-level operations (e.g., float64ToFloat16), I'll implement helper functions. C implementations may be used if high-performance tasks arise.

It's a bit odd to say that given that your second goal stated above says "C Implementation of Float16Array".

we do not need to implement specialized Math functions like Math.fround(), Math.imul(), etc., that are typically required for scalar float32 arithmetic in ECMAScript.

This is in direct conflict with your answers in 4 and 5.

Implementing proper rounding modes (e.g., rounding to nearest, truncating, etc.) will be essential.

Given that JS and C (by default) don't support alternative IEEE rounding modes, this is a curious thing to include.

General comments.

Your responses above smell of an LLM-generated response. I suggest you think more carefully both about your proposal and the questions I asked above.

[dhruvilmehta]

It's a bit odd to say that given that your second goal stated above says "C Implementation of Float16Array".

I planned for C implementation first but instead came to the ArrayBuffer solution. I am yet to update the goal for this proposal since I am updating everything in a separate doc file for the proposal.

This is in direct conflict with your answers in 4 and 5.

Sorry, I got a bit confused between Math functions and helper functions. Yes, we'll most probably need to implement some functions like f16round, float64tofloat16, float32tofloat16, etc.

Given that JS and C (by default) don't support alternative IEEE rounding modes, this is a curious thing to include.

Yes, I am still exploring this and will update the proposal accordingly.

General comments.

Your responses above smell of an LLM-generated response. I suggest you think more carefully both about your proposal and the questions I asked above.

I wrote it on my own and got the language refined by the Grammarly suggestions. Apologies for the confusion.
I am updating my previous response to be more clear. I am also gradually updating my proposal for the same.