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gptkbp:instance_of
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gptkb:microprocessor
|
|
gptkbp:application
|
gptkb:AI_technology
|
|
gptkbp:architecture
|
gptkb:tachymetric_scale
|
|
gptkbp:competes_with
|
gptkb:NVIDIA_DGX
gptkb:IBM_Watson
gptkb:Google_TPU
|
|
gptkbp:cooling_system
|
liquid cooling
|
|
gptkbp:designed_by
|
gptkb:Cerebras_Systems
|
|
gptkbp:developed_by
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gptkb:machine_learning
AI inference
deep learning research
AI training
large scale AI models
|
|
gptkbp:form_factor
|
single chip
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gptkbp:has
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high throughput
high bandwidth memory
|
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gptkbp:has_units
|
400,000
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|
https://www.w3.org/2000/01/rdf-schema#label
|
Cerebras CS-1
|
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gptkbp:is_a
|
deep learning system
|
|
gptkbp:is_a_framework_for
|
gptkb:Tensor_Flow
gptkb:Py_Torch
|
|
gptkbp:is_available_in
|
gptkb:cloud_services
data centers
|
|
gptkbp:is_influential_in
|
AI development
supercomputing advancements
deep learning evolution
|
|
gptkbp:is_known_for
|
gptkb:performance
efficiency
scalability
|
|
gptkbp:is_optimized_for
|
AI workloads
|
|
gptkbp:is_part_of
|
gptkb:Cerebras_product_line
AI hardware revolution
|
|
gptkbp:is_recognized_by
|
gptkb:technology_publications
industry awards
AI conferences
|
|
gptkbp:is_supported_by
|
Cerebras ecosystem
Cerebras software
|
|
gptkbp:is_used_in
|
gptkb:vehicles
computer vision
financial modeling
natural language processing
healthcare AI
|
|
gptkbp:market_segment
|
enterprise AI
|
|
gptkbp:notable_feature
|
largest chip ever made
|
|
gptkbp:performance
|
1.2 trillion parameters
|
|
gptkbp:power_consumption
|
20 k W
|
|
gptkbp:ram
|
2.6 TB
|
|
gptkbp:released_in
|
gptkb:2020
|
|
gptkbp:successor
|
gptkb:Cerebras_CS-2
|
|
gptkbp:target_audience
|
large enterprises
research institutions
|
|
gptkbp:uses
|
gptkb:neural_networks
deep learning
|
|
gptkbp:uses_silicon
|
gptkb:Wafer_Scale_Engine_2
|
|
gptkbp:weight
|
over 200 pounds
|
|
gptkbp:bfsParent
|
gptkb:Cerebras_Software
|
|
gptkbp:bfsLayer
|
6
|