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Found 4 papers, 1 papers with code
Scaling Deep Learning Computation over the Inter-Core Connected Intelligence Processor with T10
As AI chips incorporate numerous parallelized cores to scale deep learning (DL) computing, inter-core communication is enabled recently by employing high-bandwidth and low-latency interconnect links on the chip (e. g., Graphcore IPU).
Hardware-Assisted Virtualization of Neural Processing Units for Cloud Platforms
To maximize the resource utilization while ensuring reasonable quality of service, a natural approach is to virtualize NPUs for efficient resource sharing for multi-tenant ML services.
G10: Enabling An Efficient Unified GPU Memory and Storage Architecture with Smart Tensor Migrations
Based on this unified GPU memory and storage architecture, G10 utilizes compiler techniques to characterize the tensor behaviors in deep learning workloads.
Multi-Label Training for Text-Independent Speaker Identification
In this paper, we propose a novel strategy for text-independent speaker identification system: Multi-Label Training (MLT).
