Lecture

Accelerator-centric OS Architecture

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Description

This lecture by the instructor Mark Silberstein discusses the concept of an accelerator-centric OS architecture for omni-programmable systems, rethinking the role of CPUs in modern computers. The presentation covers topics such as the challenges of traditional CPU-centric architectures, the emergence of X-Processing Units (XPUs) for near-data processing, and the implementation of GPU-centric services. It explores the benefits of CPU-less designs, GPU-centric virtual memory management, and the potential of GPUrdma for direct GPU access to RDMA. The lecture also delves into the importance of application offload to SmartNICs in data centers and the ongoing work on the Omnix project.

Official source

Ontological neighbourhood

Computer engineering

High-performance computing: Parallel computing

Related concepts (32)

Graphics processing unit

A graphics processing unit (GPU) is a specialized electronic circuit initially designed to accelerate computer graphics and (either on a video card or embedded on the motherboards, mobile phones, personal computers, workstations, and game consoles). After their initial design, GPUs were found to be useful for non-graphic calculations involving embarrassingly parallel problems due to their parallel structure. Other non-graphical uses include the training of neural networks and cryptocurrency mining.

Central processing unit

A central processing unit (CPU)—also called a central processor or main processor—is the most important processor in a given computer. Its electronic circuitry executes instructions of a computer program, such as arithmetic, logic, controlling, and input/output (I/O) operations. This role contrasts with that of external components, such as main memory and I/O circuitry, and specialized coprocessors such as graphics processing units (GPUs). The form, design, and implementation of CPUs have changed over time, but their fundamental operation remains almost unchanged.

General-purpose computing on graphics processing units

General-purpose computing on graphics processing units (GPGPU, or less often GPGP) is the use of a graphics processing unit (GPU), which typically handles computation only for computer graphics, to perform computation in applications traditionally handled by the central processing unit (CPU). The use of multiple video cards in one computer, or large numbers of graphics chips, further parallelizes the already parallel nature of graphics processing.

CPU cache

A CPU cache is a hardware cache used by the central processing unit (CPU) of a computer to reduce the average cost (time or energy) to access data from the main memory. A cache is a smaller, faster memory, located closer to a processor core, which stores copies of the data from frequently used main memory locations. Most CPUs have a hierarchy of multiple cache levels (L1, L2, often L3, and rarely even L4), with different instruction-specific and data-specific caches at level 1.

Physics processing unit

A physics processing unit (PPU) is a dedicated microprocessor designed to handle the calculations of physics, especially in the physics engine of video games. It is an example of hardware acceleration. Examples of calculations involving a PPU might include rigid body dynamics, soft body dynamics, collision detection, fluid dynamics, hair and clothing simulation, finite element analysis, and fracturing of objects. The idea is having specialized processors offload time-consuming tasks from a computer's CPU, much like how a GPU performs graphics operations in the main CPU's place.

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