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06/06/2023
Exploiting Scratchpad Memory for Deep Temporal Blocking: A case study for 2D Jacobian 5-point iterative stencil kernel (j2d5pt)
General Purpose Graphics Processing Units (GPGPU) are used in most of th...
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05/12/2023
Revisiting Temporal Blocking Stencil Optimizations
Iterative stencils are used widely across the spectrum of High Performan...
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01/06/2023
Myths and Legends in High-Performance Computing
In this humorous and thought provoking article, we discuss certain myths...
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04/15/2022
Preparing for the Future – Rethinking Proxy Apps
A considerable amount of research and engineering went into designing pr...
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04/05/2022
Persistent Kernels for Iterative Memory-bound GPU Applications
Iterative memory-bound solvers commonly occur in HPC codes. Typical GPU ...
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10/21/2021
MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems
Scientific communities are increasingly adopting machine learning and de...
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10/19/2021
Digital transformation of droplet/aerosol infection risk assessment realized on "Fugaku" for the fight against COVID-19
The fastest supercomputer in 2020, Fugaku, has not only achieved digital...
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04/27/2021
Performance Portable Back-projection Algorithms on CPUs: Agnostic Data Locality and Vectorization Optimizations
Computed Tomography (CT) is a key 3D imaging technology that fundamental...
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10/27/2020
Matrix Engines for High Performance Computing:A Paragon of Performance or Grasping at Straws?
Matrix engines or units, in different forms and affinities, are becoming...
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08/26/2020
Scaling Distributed Deep Learning Workloads beyond the Memory Capacity with KARMA
The dedicated memory of hardware accelerators can be insufficient to sto...
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07/25/2020
The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs with Hybrid Parallelism
We present scalable hybrid-parallel algorithms for training large-scale ...
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04/11/2020
A Study of Single and Multi-device Synchronization Methods in Nvidia GPUs
GPUs are playing an increasingly important role in general-purpose compu...
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04/09/2020
A Survey on Coarse-Grained Reconfigurable Architectures from a Performance Perspective
With the end of both Dennard's scaling and Moore's law, computer users a...
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02/14/2020
High-Performance High-Order Stencil Computation on FPGAs Using OpenCL
In this paper we evaluate the performance of FPGAs for high-order stenci...
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01/06/2020
AN5D: Automated Stencil Framework for High-Degree Temporal Blocking on GPUs
Stencil computation is one of the most widely-used compute patterns in h...
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10/15/2019
The Memory Controller Wall: Benchmarking the Intel FPGA SDK for OpenCL Memory Interface
Supported by their high power efficiency and recent advancements in High...
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09/06/2019
iFDK: A Scalable Framework for Instant High-resolution Image Reconstruction
Computed Tomography (CT) is a widely used technology that requires compu...
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07/14/2019
A Versatile Software Systolic Execution Model for GPU Memory-Bound Kernels
This paper proposes a versatile high-performance execution model, inspir...
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03/27/2019
Batched Sparse Matrix Multiplication for Accelerating Graph Convolutional Networks
Graph Convolutional Networks (GCNs) are recently getting much attention ...
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02/26/2019
A New Linear Time Correctness Condition for Multiplicative Linear Logic
In this paper, we give a new linear time correctness condition for proof...
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12/21/2018
Adaptive Pattern Matching with Reinforcement Learning for Dynamic Graphs
Graph pattern matching algorithms to handle million-scale dynamic graphs...
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11/29/2018
Second-order Optimization Method for Large Mini-batch: Training ResNet-50 on ImageNet in 35 Epochs
Large-scale distributed training of deep neural networks suffer from the...
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10/22/2018
Double-precision FPUs in High-Performance Computing: an Embarrassment of Riches?
Among the (uncontended) common wisdom in High-Performance Computing (HPC...
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04/13/2018
μ-cuDNN: Accelerating Deep Learning Frameworks with Micro-Batching
NVIDIA cuDNN is a low-level library that provides GPU kernels frequently...
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04/05/2018
High-performance sparse matrix-matrix products on Intel KNL and multicore architectures
Sparse matrix-matrix multiplication (SpGEMM) is a computational primitiv...
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02/01/2018