high performance computing on graphics processing units: hgpu.org

Jeffrey Krupa, Kelvin Lin, Maria Acosta Flechas, Jack Dinsmore, Javier Duarte, Philip Harris, Scott Hauck, Burt Holzman, Shih-Chieh Hsu, Thomas Klijnsma, Mia Liu, Kevin Pedro, Natchanon Suaysom, Matt Trahms, Nhan Tran

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Tags: Deep learning, FPGA, HEP, nVidia, Package, Physics, Tesla T4, Tesla V100

July 26, 2020 by hgpu

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Specx: Speculative task-based runtime system

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

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high performance computing on graphics processing units: hgpu.org

It’s all about data movement: Optimising FPGA data access to boost performance

An OpenCL 3D FFT for Molecular Dynamics Simulations on Multiple FPGAs

LoopBench: An Evaluation of Loop Acceleration in Heterogeneous Systems

Extending High-Level Synthesis for Task-Parallel Programs

Adaptation of High Performance and High Capacity Reconfigurable Systems to OpenCL Programming Environments

Towards Efficient and Scalable Acceleration of Online Decision Tree Learning on FPGA

Heterogeneity-Aware Cluster Scheduling Policies for Deep Learning Workloads

Compiler-Based Tools to Aid in Data Transfer Optimization and On-Chip Debug of Heterogeneous Compute Systems

Modular FPGA Systems with Support for Dynamic Workloads and Virtualisation

AnyHLS: High-Level Synthesis with Partial Evaluation

EDSSA: An Encoder-Decoder Semantic Segmentation Networks Accelerator on OpenCL-Based FPGA Platform

GPU coprocessors as a service for deep learning inference in high energy physics

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