Statements (76)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:architecture
|
| gptkbp:competes_with |
gptkb:AMD_Vega_architecture
|
| gptkbp:designed_by |
gptkb:NVIDIA
|
| gptkbp:enables |
deep learning applications
|
| gptkbp:features |
high-performance computing
|
| https://www.w3.org/2000/01/rdf-schema#label |
Titan architecture
|
| gptkbp:includes |
gptkb:NVLink_technology
|
| gptkbp:is_adopted_by |
startups and enterprises
high-performance applications major research institutions |
| gptkbp:is_available_in |
various configurations
|
| gptkbp:is_based_on |
gptkb:Volta_architecture
|
| gptkbp:is_compared_to |
previous architectures
other GPU architectures |
| gptkbp:is_compatible_with |
NVIDIA software stack
|
| gptkbp:is_discussed_in |
technology forums
|
| gptkbp:is_documented_in |
research papers
technical whitepapers |
| gptkbp:is_enhanced_by |
software optimizations
|
| gptkbp:is_evaluated_by |
performance metrics
energy consumption industry standards cost-effectiveness benchmark tests |
| gptkbp:is_featured_in |
technology reviews
NVIDIA conferences |
| gptkbp:is_integrated_with |
data centers
cloud computing platforms AI development tools AI platforms |
| gptkbp:is_known_for |
high computational power
|
| gptkbp:is_optimized_for |
AI workloads
|
| gptkbp:is_part_of |
gptkb:NVIDIA_GPU_family
NVIDIA's research initiatives NVIDIA's product lineup |
| gptkbp:is_prominent_in |
gptkb:academic_research
machine learning conferences |
| gptkbp:is_promoted_by |
NVIDIA marketing campaigns
|
| gptkbp:is_promoted_through |
partnerships
|
| gptkbp:is_recognized_as |
a breakthrough in GPU technology
|
| gptkbp:is_recognized_by |
industry experts
|
| gptkbp:is_recognized_for |
energy efficiency
scalability its impact on technology flexibility in applications |
| gptkbp:is_supported_by |
gptkb:developers
NVIDIA's ecosystem NVIDIA drivers NVIDIA's training resources NVIDIA's technical support |
| gptkbp:is_targeted_at |
research and data science
|
| gptkbp:is_tested_for |
academic settings
real-world scenarios machine learning frameworks AI benchmarks |
| gptkbp:is_used_for |
data analysis
|
| gptkbp:is_used_in |
scientific simulations
|
| gptkbp:is_utilized_by |
AI researchers
|
| gptkbp:is_utilized_for |
image processing
natural language processing |
| gptkbp:is_utilized_in |
financial modeling
supercomputers healthcare analytics robotics applications |
| gptkbp:manufacturer |
12 nm process technology
|
| gptkbp:predecessor |
gptkb:Ampere_architecture
|
| gptkbp:provides |
16 GB HBM2 memory
|
| gptkbp:released_in |
gptkb:2018
|
| gptkbp:successor |
gptkb:Pascal_architecture
|
| gptkbp:supports |
gptkb:Tensor_Cores
CUDA programming model |
| gptkbp:used_in |
gptkb:NVIDIA_Titan_V
|
| gptkbp:bfsParent |
gptkb:The_Ulduar_Raid
gptkb:Ulduar_Raid gptkb:The_Storm_Peaks |
| gptkbp:bfsLayer |
6
|