Awesome-GPU
Awesome resources for GPUs
https://github.com/Jokeren/Awesome-GPU
Last synced: 3 days ago
JSON representation
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Tools
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Profilers
- **HPCToolkit**
- **NVIDIA Nsight Systems**
- **NVIDIA Nsight Compute**
- **SASSI**
- **NVBit**
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- **Vampir|Score-P**
- **TAU**
- **Open|SpeedShop**
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Exposing Hidden Performance Opportunities in High Performance GPU Applications
- Lynx: A dynamic instrumentation system for data-parallel applications on GPGPU architectures
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
- Monitoring Heterogeneous Applications with the OpenMP Tools Interface
- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes
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Benchmarking
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Models
- Instruction Roofline An insightful visual performance model for GPUs
- Performance Tuning of Scientific Codes with the Roofline Model
- Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
- Fundamental_Optimizations
- Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
- Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
- Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
- Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
- Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
- Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
- Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
- Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
- Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
- Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
- Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
- Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
- Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
- Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
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Simulators
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Architecture
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Resources Management
- Dynamic GPGPU Power Management Using Adaptive Model Predictive Control
- Transparent Offloading and Mapping (TOM): Enabling Programmer-Transparent Near-Data Processing in GPU Systems
- Reducing Energy in GPGPUs through Approximate Trivial Bypassing
- Locality-Aware CTA Clustering for Modern GPUs
- Dynamic Resource Management for Efficient Utilization of Multitasking GPUs
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Parallelism
- Accelerate GPU Concurrent Kernel Execution by Mitigating Memory Pipeline Stalls
- Controlled Kernel Launch for Dynamic Parallelism in GPUs
- LaPerm: Locality Aware Scheduler for Dynamic Parallelism on GPUs
- Virtual Thread Maximizing Thread-Level Parallelism beyond GPU Scheduling Limit
- Understanding Latency Hiding on GPUs
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Cache
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Memory
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White Papers
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Algorithms
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BLAS
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Stencils
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Scans
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Applications
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Runtime
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Code Generation
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Compilers
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Programming Models
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Profile Guided Optimization
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Binaries
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