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A Graph-based Model for GPU Caching Problems

Lingda Li, Ari B. Hayes, Stephen A. Hackler, Eddy Z. Zhang, Mario Szegedy, Shuaiwen Leon Song

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 680, Task scheduling

May 9, 2016 by hgpu

Exposing Errors Related to Weak Memory in GPU Applications

Tyler Sorensen, Alastair F. Donaldson

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 770, nVidia GeForce GTX 980, nVidia GeForce GTX Titan, nVidia Quadro K5200, Tesla C2050, Tesla C2075, Tesla K20

May 3, 2016 by hgpu

A Survey of Cache Bypassing Techniques

Sparsh Mittal

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Tags: cache bypassing, cpu, CPU-GPU heterogeneous system, DRAM, GPU, Memory, non-volatile memory, survey

April 29, 2016 by sparsh0mittal

A Survey Of Architectural Techniques for Managing Process Variation

Sparsh Mittal

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Tags: cache, computer architecture, cpu, DVFS, GPU, Memory, survey

December 6, 2015 by sparsh0mittal

Heterogeneous CPU/(GP) GPU Memory Hierarchy Analysis and Optimization

Josue Vladimir Quiroga Esparza

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Tags: Computer science, CUDA, Heterogeneous systems, Memory, nVidia, Thesis

November 4, 2015 by hgpu

Adaptive and Transparent Cache Bypassing for GPUs

Ang Li, Gert-Jan van den Braak, Akash Kumar, Henk Corporaal

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Tags: Benchmarking, cache, Computer science, Memory, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 570, nVidia GeForce GTX 690, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX 980, Performance, PTX, Tesla K40, Tesla K80

September 24, 2015 by hgpu

A Survey Of Architectural Techniques for Near-Threshold Computing

Sparsh Mittal

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Tags: cpu, Energy-efficient computing, low voltage computing, Memory, Power-efficient computing, survey

September 7, 2015 by sparsh0mittal

A Survey Of Techniques for Architecting DRAM Caches

Sparsh Mittal, Jeffrey Vetter

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Tags: 3D DRAM, bandwidth, cpu, die-stacking, GPU, Memory, survey

August 7, 2015 by sparsh0mittal

A Survey of Software Techniques for Using Non-Volatile Memories for Storage and Main Memory Systems

Sparsh Mittal and Jeffrey S. Vetter

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Tags: cpu, flash, high performance computing, Memory, non-volatile memory, storage, supercomputer

June 3, 2015 by sparsh0mittal

Model-driven optimisation of memory hierarchy and multithreading on GPUs

Andrew A. Haigh, Eric C. McCreath

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 580, Tesla K20

March 2, 2015 by hgpu

Exploring Design Space of 3D NVM and eDRAM Caches Using DESTINY Tool (open-source code)

Sparsh Mittal, Matt Poremba, Jeffrey Vetter, Yuan Xie

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Source codes

Tags: Architecture, area, cache, cpu, energy, GPGPU, latency modeling, Memory, Package

February 22, 2015 by sparsh0mittal

A Survey of Power Management Techniques for Phase Change Memory

Sparsh Mittal

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Tags: cpu, Energy-efficient computing, GPU, Memory, non-volatile memory, Power-efficient computing

February 3, 2015 by sparsh0mittal

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

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

See all packages

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high performance computing on graphics processing units: hgpu.org

A Graph-based Model for GPU Caching Problems

Exposing Errors Related to Weak Memory in GPU Applications

A Survey of Cache Bypassing Techniques

A Survey Of Architectural Techniques for Managing Process Variation

Heterogeneous CPU/(GP) GPU Memory Hierarchy Analysis and Optimization

Adaptive and Transparent Cache Bypassing for GPUs

A Survey Of Architectural Techniques for Near-Threshold Computing

A Survey Of Techniques for Architecting DRAM Caches

A Survey of Software Techniques for Using Non-Volatile Memories for Storage and Main Memory Systems

Model-driven optimisation of memory hierarchy and multithreading on GPUs

Exploring Design Space of 3D NVM and eDRAM Caches Using DESTINY Tool (open-source code)

A Survey of Power Management Techniques for Phase Change Memory

Recent source codes

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

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

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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

SIGMo: Scalable Isomorphism Graph Matching on GPUs

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

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