The devices people rely on every day (smartphones, laptops, cloud servers, etc.) are constantly evolving to handle more demanding tasks, whether it’s running high-performance apps, processing large datasets, or supporting advanced AI functions.
But as the capabilities of these devices improve, the architecture powering them faces growing pressure to keep up. These systems, made of processors, memory units, and complex software, must be able to work faster, manage larger amounts of data, and remain efficient around the clock — all without wasting energy or overheating.
This is what Ananya Pareek is tackling head-on. As a performance engineer with experience at Apple, Samsung, and Google, Ananya has been in charge of building tools that identify and fix inefficiencies in modern computing systems for many years. From developing modeling systems that predict the efficiency and performance of future hardware systems to creating data analysis platforms for identifying patterns and guiding current system designs, Ananya has helped some of the biggest tech companies in the world improve their systems to deliver powerful, sustainable products to millions of users.
Read on to find out how Ananya is building stronger, more efficient computer architectures across the tech industry.
Ananya’s engineering background
Ananya’s fascination with the technology behind electronic systems began while studying at the Indian Institute of Technology Kanpur, where he earned a Bachelor’s in Electrical Engineering. Driven by an interest in understanding how systems like CPUs power devices such as computers, Ananya pursued a Master’s in Computer Engineering at the University of Rochester, where he was awarded the Frank J. Horton Fellowship to work on optimizing the performance of particle physics simulators — specialized computer programs that predict how particles would behave in different experimental scenarios.
After graduating, Ananya began working for MIPS (Imagination Technologies), a semiconductor firm designing chips for digital devices. This was Ananya’s first real exposure to the complex processes behind the technology powering laptops, smartphones, and other digital products.
Gaining this insight into how technology works at a deeper level sparked a lasting interest and commitment to improving these systems on a larger scale for Ananya. That commitment is especially relevant today as the tech industry continues to expand the capabilities of digital devices, from the widespread adoption of AI by companies like Microsoft and Meta to the expansion of cloud storage servers.
While these advancements effectively enhance products used by millions of people around the world, they also place significant pressure on the underlying systems supporting them. Without the capacity to support larger applications and process the vast amounts of data that go with them, these devices risk costly issues like overheating, freezing, or even shutting down, which affects both users and businesses.
The market for high-performance computing systems has grown from $37 billion in 2020 to $49.4 billion in 2025, showing an industry-wide need for more efficient, scalable infrastructures that can meet these increasing demands.
Ananya’s work seeks to address these challenges by ensuring that computing systems can handle larger and more complex tasks and are able to scale effectively as these demands continue to grow.
Setting performance benchmarks for Mac Systems
In 2019, Ananya joined Apple as a System Performance Architect, where he played a key role in the development of the company’s new Mac product line. At the time, Apple was preparing to transition its latest MacBook and iPad models to the advanced M1 chip — a shift that required seamless integration with their software to ensure the products could meet the company’s high-performance targets while staying within strict power consumption and heat generation limits.
To help achieve this balance, Ananya created a set of tools that would predict the system power and performance expectations based on a set of representative benchmarks. Built using Python, these tools simulated real-world scenarios, analyzed the test data to measure the system’s performance, and identified operational bottlenecks. By pinpointing which processes were putting the most strain on the device, engineers could address inefficiencies well ahead of time.
Ananya’s contributions ultimately played a vital role in Apple’s successful shift to the M1 chip. Launched in 2020, this chip delivered significant operational improvements, including up to 3.5 times faster CPU performance, up to 6 times better GPU performance, and twice the battery life of its predecessors — solidifying Apple’s reputation for powerful yet efficient devices.
Expanding GPU capabilities at Samsung
After his success at Apple, Ananya joined Samsung in 2022 as a GPU Performance Architect, where he was tasked with improving the performance and efficiency of the company’s Xclipse mobile GPUs, which were being integrated into Galaxy smartphones. These GPUs, responsible for rendering graphics in applications like video games and social media, needed to provide high-quality visual performance without exhausting the phone’s power consumption so as to ensure longer battery life.
Ananya tackled this by designing a series of performance simulators and debugging tools that could test the GPU’s performance under real-world conditions. These tools allowed Samsung engineers to pinpoint performance inefficiencies in real-time, enabling quick fixes before minor issues turned into costly problems. They also worked closely with hardware and software teams to test the performance of Xclipse’s shader components, the GPU’s component responsible for rendering light, colors, and textures in 3D visuals — further improving the quality of the phone’s graphics.
Through these efforts, Ananya contributed to the success of Samsung’s in-house GPUs, helping the company’s newest generation of smartphones deliver both high-quality visuals and longer battery life.
Delivering sustainable computer architectures
Ananya is currently a software engineer for ML performance at Google, where he focuses on predicting and optimizing the performance of machine learning models. As this technology becomes a more integral part of Google’s operations, Ananya contributes to creating hardware roadmaps that facilitate this integration, ensuring services like the company’s Gemini chatbot can perform efficiently at scale in a cost-effective manner.
Ananya Pareek’s work in computer architecture is empowering major tech companies to build resilient system infrastructures that can support large-scale applications without sacrificing their high-performance standards. By developing tools that thoroughly test system performance, resolve potential issues before they escalate, and extend battery life, he’s setting the groundwork for stronger, more reliable products, enabling businesses to meet the demands of modern technology while delivering high-quality services to millions of users worldwide.
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