Paper
:
BSTC: A Novel Binarized-Soft-Tensor-Core Design for Accelerating Bit-Based Approximated Neural Nets
Event Type
Paper
Registration Categories
TP
Tags
Applications
Data Management
Deep Learning
GPUs
Machine Learning
Performance
Scalable Computing
TimeWednesday, 20 November 201911:30am - 12pm
DescriptionWe propose binarized-soft-tensor-core as a software-hardware co-design approach to construct the bit-manipulation capability for modern GPUs to effectively harvest the emerging bit-level-parallelism from BNNs and a variety of domains. We propose intra- and inter-layer fusion techniques so that the entire BNN inference process can be realized in one GPU kernel, labeled as Singular-Binarized-Neural-Network. Experiments show that our design can achieve over 1000x speedup for raw inference latency and 10x for inference throughput over state-of-the-art full-precision simulated BNN inference for AlexNet on ImageNet.
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