What is recorded here?
Integrated multi-GPU execution and architecture-aware inference with CPU/NVMe offloading to support dense and expert Transformer models under different latency and throughput constraints.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Performance and model-capacity figures depend on hardware, workloads and resource budgets. Distributed trillion-parameter inference is not single-GPU capability. Original training-side ZeRO and later FastGen remain separate.
Read the original work
- DeepSpeed Inference: Enabling Efficient Inference of Transformer Models at Unprecedented Scale
- Aminabadi et al.: DeepSpeed dense, sparse and heterogeneous inference — official research record
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
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People and systems
Reza Yazdani Aminabadi; Samyam Rajbhandari; Minjia Zhang; Ammar Ahmad Awan; Cheng Li; Du Li; Elton Zheng; Jeff Rasley; Shaden Smith; Olatunji Ruwase; Yuxiong He
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
Aminabadi et al.: DeepSpeed dense, sparse and heterogeneous inference
Integrated multi-GPU execution and architecture-aware inference with CPU/NVMe offloading to support dense and expert Transformer models under different latency and throughput constraints.
Scientific scope
Performance and model-capacity figures depend on hardware, workloads and resource budgets. Distributed trillion-parameter inference is not single-GPU capability. Original training-side ZeRO and later FastGen remain separate.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Reza Yazdani Aminabadi; Samyam Rajbhandari; Minjia Zhang; Ammar Ahmad Awan; Cheng Li; Du Li; Elton Zheng; Jeff Rasley; Shaden Smith; Olatunji Ruwase; Yuxiong He
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.