Vivek Angoth
Vivek Angoth is a Senior System Software Engineer at NVIDIA, where he develops foundational system-software components for the company’s autonomous-vehicle platform. His work spans error-reporting frameworks, safety-driven degradation paths, and ISO 26262 ASIL-D–compliant embedded software across real-time operating systems such as QNX and internal RTOS environments. Vivek collaborates closely with architecture, safety, and customer engineering teams to deliver highly reliable software for L2–L3 autonomous driving.
Before joining NVIDIA, Vivek worked as a Firmware Engineer at Apple, contributing to the architecture, bootloader, and low-level firmware for Apple's Display and Touch chips. He previously spent several years at Intel, where he focused on SSD firmware, FTL design, performance micro-architecture, and NAND media policy. His work earned multiple divisional awards and resulted in two issued patents related to storage-performance optimization.
Vivek holds an MS in Electrical and Computer Engineering from the University of Colorado Boulder and a B.Tech in Electronics and Communication Engineering from NIT Warangal.
Optimizing Performance in Embedded Systems: Techniques for Working Within Real-World Constraints
Status: Coming up in April 2026!CPU cycles are often the most precious resource in an embedded system, and understanding how to use them efficiently can dramatically improve performance, responsiveness, and system stability. This talk focuses on practical, foundational techniques to analyze and optimize CPU utilization in real-world embedded environments.
We begin by examining how to detect whether the CPU, memory, or power subsystem is limiting system performance—with an emphasis on interpreting CPU load, idle time, task scheduling behavior, and profiling data. The session then dives deeper into proven CPU optimization approaches: scheduling improvements, reducing context-switch overhead, identifying hotspots, loop unrolling, caching strategies, data-layout tuning, and other techniques that help squeeze more useful work out of limited hardware.
While the focus is CPU-first, we also cover key memory and power constraints and how they interact with CPU execution, helping developers avoid shifting bottlenecks from one subsystem to another.
This talk is primarily theoretical but supported by selective real-world examples from complex embedded systems. Attendees will walk away with a clear framework for identifying bottlenecks and a practical toolkit of optimization techniques to improve performance on constrained embedded platforms.