Compute for India: A Measured Approach

Amlan Mohanty

Source Link

Introduction

Compute, as we explain in our primer, is used to refer to many things—the capacity to perform complex calculations, specific hardware equipment like semiconductors, or as a unit of measurement expressed in floating-point operations per second (FLOPS) that quantifies a computer’s ability to execute high-performance tasks like machine learning.

A more holistic view of compute positions it as a technology stack comprising three layers—a hardware, a software, and an infrastructure layer. Collectively, this forms what has come to be known as the “compute stack,” which may include:

• Advanced chips (GPUs, TPUs)
• Specialised software to run the chips (compute unified device architecture or CUDA)
• Data centers and network infrastructure (Google, AWS, Azure)
• Data storage and management software (Oracle, IBM, SAP)
• Machine learning frameworks and programming languages (PyTorch)

Compute is central to the IndiaAI mission. In March 2024, the Cabinet allocated Rs. 10,372 crores ($1.3 billion) for the mission, nearly half of which, about Rs. 4,568 crores, has been earmarked to build compute capacity across the country. This demonstrates the importance of compute to India’s growing AI ambitions.