GPUs Insights | Sumble

What is GPUs?

GPUs (Graphics Processing Units) are specialized electronic circuits designed to rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device. They are commonly used in embedded systems, mobile phones, personal computers, workstations, and game consoles. Modern GPUs are very efficient at manipulating computer graphics and image processing, and their highly parallel structure makes them more effective than general-purpose CPUs for algorithms where processing of large blocks of data is done in parallel.

Find organizations using GPUs on Sumble →

What other technologies are related to GPUs?

GPUs Competitor Technologies

TPUs

Tensor Processing Units are custom ASICs developed by Google specifically for machine learning tasks, making them a direct competitor to GPUs in certain applications.

mentioned alongside GPUs in 61% (294) of relevant job posts

CPUs

Central Processing Units can perform general-purpose computations and can be used for tasks that overlap with GPUs, although GPUs are generally preferred for parallelizable workloads. CPUs serve as a competitor where GPU's cannot be used.

mentioned alongside GPUs in 43% (389) of relevant job posts

NPUs

Neural Processing Units are specialized hardware accelerators designed for neural network inference, competing with GPUs in edge computing and AI inference applications.

mentioned alongside GPUs in 61% (94) of relevant job posts

FPGAs

Field-Programmable Gate Arrays can be configured to perform specific computations, including those traditionally handled by GPUs. FPGAs offer reconfigurability, making them a competitor in niche applications.

mentioned alongside GPUs in 6% (642) of relevant job posts

DSPs

Digital Signal Processors are specialized for signal processing tasks and can be a competitor in certain embedded systems and specific applications where GPUs might be overkill.

mentioned alongside GPUs in 3% (209) of relevant job posts

ASICs

Application-Specific Integrated Circuits are designed for specific tasks. ASICs are a competitor to GPUs because GPUs are not specific to any task.

mentioned alongside GPUs in 5% (112) of relevant job posts

ARM processors

ARM processors compete with GPUs for embedded applications and energy-efficient computing where GPU acceleration may not be necessary or practical.

mentioned alongside GPUs in 7% (72) of relevant job posts

GPUs Complementary Technologies

DPUs

Data Processing Units are designed to offload infrastructure tasks from CPUs and GPUs, enhancing the overall system performance by working in conjunction with GPUs.

mentioned alongside GPUs in 39% (79) of relevant job posts

MPI

Message Passing Interface is a communication protocol used in parallel computing, complementing GPUs by enabling distributed computation across multiple GPU-equipped nodes.

mentioned alongside GPUs in 3% (197) of relevant job posts

NCCL

NVIDIA Collective Communications Library accelerates collective communication primitives for multi-GPU and multi-node training, directly complementing GPU usage in distributed deep learning.

mentioned alongside GPUs in 6% (61) of relevant job posts