NCCL
E209960
NCCL (NVIDIA Collective Communications Library) is a high-performance library that optimizes multi-GPU and multi-node communication for deep learning and HPC applications.
All labels observed (3)
| Label | Occurrences |
|---|---|
| NCCL canonical | 2 |
| NVIDIA Collective Communications Library | 1 |
| NVIDIA NCCL | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T1893382 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
Target entity: NCCL Context triple: [NVIDIA CUDA, includes, NCCL]
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A.
NVIDIA CUDA
NVIDIA CUDA is a parallel computing platform and programming model that enables developers to use NVIDIA GPUs for general-purpose high-performance computing.
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B.
NVIDIA AI Enterprise software suite
NVIDIA AI Enterprise software suite is a comprehensive, enterprise-grade collection of AI tools, frameworks, and optimized software designed to accelerate the development and deployment of AI and data analytics workloads across modern data centers and clouds.
-
C.
GPU
The GPU (State Political Directorate) was the Soviet Union’s early secret police and intelligence agency that operated in the 1920s, overseeing political repression and internal security before later reorganizations.
-
D.
GPU
GPU is the vehicle registration code used on license plates for cars registered in Poland’s Pomeranian Voivodeship.
-
E.
PlaidML
PlaidML is an open-source, hardware-agnostic deep learning engine designed to accelerate neural network computation on a wide range of GPUs and other devices.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: NCCL Target entity description: NCCL (NVIDIA Collective Communications Library) is a high-performance library that optimizes multi-GPU and multi-node communication for deep learning and HPC applications.
-
A.
NVIDIA CUDA
NVIDIA CUDA is a parallel computing platform and programming model that enables developers to use NVIDIA GPUs for general-purpose high-performance computing.
-
B.
NVIDIA AI Enterprise software suite
NVIDIA AI Enterprise software suite is a comprehensive, enterprise-grade collection of AI tools, frameworks, and optimized software designed to accelerate the development and deployment of AI and data analytics workloads across modern data centers and clouds.
-
C.
GPU
The GPU (State Political Directorate) was the Soviet Union’s early secret police and intelligence agency that operated in the 1920s, overseeing political repression and internal security before later reorganizations.
-
D.
GPU
GPU is the vehicle registration code used on license plates for cars registered in Poland’s Pomeranian Voivodeship.
-
E.
PlaidML
PlaidML is an open-source, hardware-agnostic deep learning engine designed to accelerate neural network computation on a wide range of GPUs and other devices.
- F. None of above. chosen
Statements (66)
| Predicate | Object |
|---|---|
| instanceOf |
GPU communication library
ⓘ
collective communications library ⓘ communication library ⓘ parallel computing library ⓘ |
| developer |
NVIDIA Corporation
ⓘ
surface form:
NVIDIA
|
| domain |
deep learning
ⓘ
distributed training ⓘ high-performance computing ⓘ multi-GPU computing ⓘ multi-node computing ⓘ |
| feature |
GPUDirect RDMA support
ⓘ
asynchronous communication API ⓘ grouped collective operations ⓘ hierarchical collectives ⓘ multi-process communication support ⓘ ring-based collectives ⓘ topology-aware communication algorithms ⓘ tree-based collectives ⓘ |
| fullName |
NCCL
self-linksurface differs
ⓘ
surface form:
NVIDIA Collective Communications Library
|
| goal |
high-bandwidth GPU communication
ⓘ
low-latency collective operations ⓘ scalable multi-GPU training ⓘ |
| integratesWith |
NVIDIA CUDA
ⓘ
surface form:
CUDA
|
| license | BSD-style license ⓘ |
| optimizedFor |
GPU interconnects
ⓘ
Nvidia Maxwell GPU ⓘ
surface form:
NVIDIA GPUs
|
| primaryAPIStyle | C API ⓘ |
| programmingLanguage | C ⓘ |
| provider |
NVIDIA Corporation
ⓘ
surface form:
NVIDIA
|
| requires | CUDA-enabled GPU ⓘ |
| supportsDataType |
bfloat16
ⓘ
float16 ⓘ float32 ⓘ float64 ⓘ int32 ⓘ int64 ⓘ uint8 ⓘ |
| supportsEnvironment |
cloud GPU clusters
ⓘ
on-premise clusters ⓘ |
| supportsHardware |
Ethernet
ⓘ
InfiniBand ⓘ NVLink interconnect ⓘ
surface form:
NVLink
NVLink interconnect ⓘ
surface form:
NVSwitch
PCI Express ⓘ
surface form:
PCIe
|
| supportsLanguageBinding |
C++
ⓘ
Python ⓘ |
| supportsOperation |
all-gather
ⓘ
all-reduce ⓘ broadcast ⓘ gather ⓘ reduce ⓘ reduce-scatter ⓘ scatter ⓘ |
| supportsReductionOp |
max
ⓘ
min ⓘ product ⓘ sum ⓘ |
| supportsTopology |
multi-node multi-GPU
ⓘ
single-node multi-GPU ⓘ |
| targetUser |
HPC developers
ⓘ
deep learning framework developers ⓘ |
| usedBy |
DeepSpeed
ⓘ
Horovod ⓘ Megatron-LM ⓘ PyTorch ⓘ
surface form:
PyTorch distributed
TensorFlow distributed training ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Subject: NCCL Description of subject: NCCL (NVIDIA Collective Communications Library) is a high-performance library that optimizes multi-GPU and multi-node communication for deep learning and HPC applications.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.