Google TPU

GPTKB entity

Statements (60)
Predicate Object
gptkbp:instance_of gptkb:Tensor_Flow
gptkbp:architecture application-specific integrated circuit (ASIC)
gptkbp:available_in gptkb:Google_Cloud_Platform
gptkbp:available_on virtual machines
bare metal
gptkbp:can_be_used_in data centers
edge devices
gptkbp:competes_with gptkb:NVIDIA_GPUs
gptkbp:designed_for gptkb:AI_technology
gptkbp:developed_by gptkb:Google
gptkbp:enables faster training of models
inference at scale
gptkbp:features matrix multiplication
high bandwidth memory
gptkbp:first_generation gptkb:TPU_v4
gptkb:TPU_v3
gptkb:TPU_v1
gptkb:TPU_v2
gptkbp:has multiple cores
gptkbp:has_performance_advantage_over traditional CPUs
general-purpose GPUs
https://www.w3.org/2000/01/rdf-schema#label Google TPU
gptkbp:introduced_in gptkb:2016
gptkbp:is_a_framework_for gptkb:JAX
gptkb:Py_Torch
gptkbp:is_available_in various configurations
gptkbp:is_compatible_with gptkb:Kubernetes
gptkb:Docker
gptkbp:is_considered_as leading AI accelerator
gptkbp:is_designed_to accelerate deep learning
gptkbp:is_integrated_with gptkb:Google_services
gptkbp:is_known_for energy efficiency
cost-effectiveness
high efficiency
gptkbp:is_optimized_for large-scale machine learning
neural network workloads
gptkbp:is_part_of Google AI ecosystem
AI hardware accelerators
Google's AI strategy
gptkbp:is_scalable thousands of chips
gptkbp:is_supported_by Google Cloud AI services
gptkbp:is_used_by large enterprises
research institutions
startups
gptkbp:is_used_for image recognition
speech recognition
recommendation systems
gptkbp:is_used_in computer vision
natural language processing
reinforcement learning
gptkbp:provides low latency
high throughput
gptkbp:supports gptkb:Tensor_Flow
gptkbp:used_for gptkb:machine_learning
gptkbp:uses custom hardware
gptkbp:bfsParent gptkb:ARM_Ethos_NPUs
gptkb:Cerebras_Wafer_Scale_Engine_2
gptkb:NVIDIA_T4_GPUs
gptkb:AWS_Inferentia
gptkbp:bfsLayer 6