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Archive 2017 - 2018

Embedded Parallelization Tooling

Yocto Integration for Multi-Core Analysis

Technology later acquired by Xilinx → AMD

8x

Speedup

6

Architectures

4

Demo Apps

Embedded Parallelization Tooling

The Problem

Demanding embedded applications (autonomous driving, 5G, avionics) require multi-core platforms, but there's no "multi-core compiler." Developers spent significant time on manual parallelization analysis. The analysis tools couldn't process applications built with Yocto Project - blocking entry into the AUTOSAR Adaptive Platform market for autonomous vehicles.

The Solution

Developed custom Yocto layers (meta-slx-toolchain, meta-slx-demos) that integrate instrumentation into the BitBake build process. Created toolchain wrappers that intercept compilation to instrument binaries for parallelization analysis. Demonstrated end-to-end AUTOSAR Adaptive application analysis for an autonomous driving use case including lane detection, vehicle detection, and emergency braking.

Tech Stack

Build Systems

Yocto ProjectBitBakeCMakeMake

Compilers

LLVM/ClangGCC Cross-compilersLinaro Toolchain

Languages

BashC/C++BitBake Metadata

Platforms

ARM (32/64)MIPSPowerPCx86/x86-64QEMU

Automotive

AUTOSAR AdaptiveOpenCVSOME/IP

My Role: Software Engineering Intern

  • Designed and implemented meta-slx-toolchain Yocto layer architecture
  • Built toolchain wrapper scripts handling cross-compilation for 6 architectures
  • Developed linker wrapper for profiling library integration
  • Created remote trace collection scripts for embedded target analysis
  • Ported 4 demo applications to Yocto build system
  • Demonstrated full AUTOSAR Adaptive application analysis for autonomous driving

Key Differentiators

First Integration: Enabled analysis tools to process Yocto-built applications

Multi-Architecture: ARM, MIPS, PowerPC, x86 - all major embedded processor families

AUTOSAR Adaptive: Cutting-edge automotive standard integration (pre-finalization)

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