Efficient Management of Scratch-Pad Memories in Deep Learning AcceleratorsSubhankar PalSwagath Venkataramaniet al.2021ISPASS 2021
A 7nm 4-Core AI Chip with 25.6TFLOPS Hybrid FP8 Training, 102.4TOPS INT4 Inference and Workload-Aware ThrottlingAnkur AgrawalSaekyu Leeet al.2021ISSCC 2021
Value Similarity Extensions for Approximate Computing in General-Purpose ProcessorsYounghoon KimSwagath Venkataramaniet al.2021DATE 2021
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training Chia-Yu ChenJiamin Niet al.2020NeurIPS 2020
Efficient AI System Design with Cross-Layer Approximate ComputingSwagath VenkataramaniXiao Sunet al.2020Proceedings of the IEEE
A 3.0 TFLOPS 0.62V Scalable Processor Core for High Compute Utilization AI Training and InferenceJinwook OhSae Kyu Leeet al.2020VLSI Circuits 2020
DyVEDeep: Dynamic Variable Effort Deep Neural NetworksSanjay GanapathySwagath Venkataramaniet al.2020ACM TECS
Hybrid 8-bit floating point (HFP8) training and inference for deep neural networksXiao SunJungwook Choiet al.2019NeurIPS 2019
Memory and Interconnect Optimizations for Peta-Scale Deep Learning SystemsSwagath VenkataramaniVijayalakshmi Srinivasanet al.2019HiPC 2019
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09 Jan 2023US11551054System-aware Selective Quantization For Performance Optimized Distributed Deep Learning
29 Aug 2022US11429524Optimized Hierarchical Scratchpads For Enhanced Artificial Intelligence Accelerator Core Utilization
MOMori OharaDeputy Director, IBM Research Tokyo, Distinguished Engineer, Chief SW Engineer for Hybrid Cloud on IBM HW