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Cao Zongyan's Projects

avxtoneon icon avxtoneon

In this project, the frequently used AVX instructions are encapsulated as independent modules to reduce repeated development workload.

efficient_transformer icon efficient_transformer

Scaling Transformer architectures has been critical for pushing the frontiers of Language Modelling (LM), a problem central to Natural Language Processing (NLP) and Language Understanding. Although there is a direct positive relationship between the Transformer capacity and its LM performance, there are practical limitations which make training massive models impossible. These limitations come in the form of computation and memory costs which cannot be solely addressed by training on parallel devices. In this thesis, we investigate two approaches which can make Transformers more computationally and memory efficient. First, we introduce the Mixture-of-Experts (MoE) Transformer which can scale its capacity at a sub-linear computational cost. Second, we present a novel content-based sparse attention mechanism called Hierarchical Self Attention (HSA). We demonstrate that the MoE Transformer is capable of achieving lower test perplexity values than a vanilla Transformer model with higher computational demands. Language Modelling experiments, involving a Transformer which uses HSA in place of conventional attention, revealed that HSA can speed up attention computation by up to 330% at a negligible cost in model performance.

legion icon legion

The Legion Parallel Programming System

mixture-of-experts icon mixture-of-experts

PyTorch Re-Implementation of "The Sparsely-Gated Mixture-of-Experts Layer" by Noam Shazeer et al. https://arxiv.org/abs/1701.06538

nccl icon nccl

Optimized primitives for collective multi-GPU communication

nmaker icon nmaker

A heterogeneous cosmological N-Body simulation code for multicore (CPU) and manycore (MIC) platforms.

paddle icon paddle

PArallel Distributed Deep LEarning

tensorflow icon tensorflow

Computation using data flow graphs for scalable machine learning

tensorrt icon tensorrt

TensorRT is a C++ library that facilitates high performance inference on NVIDIA GPUs and deep learning accelerators.

transformer icon transformer

A TensorFlow Implementation of the Transformer: Attention Is All You Need

vllm icon vllm

A high-throughput and memory-efficient inference and serving engine for LLMs

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