GPU

MOST: Memory Oversubscription-Aware Scheduling for Tensor Migration on GPU Unified Storage
Deep Neural Network (DNN) training demands large memory capacities that exceed the limits of current GPU onboard memory. Expanding GPU …
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MOST: Memory Oversubscription-Aware Scheduling for Tensor Migration on GPU Unified Storage
SSFFT: Energy-Efficient Selective Scaling for Fast Fourier Transform in Embedded GPUs
Fast Fourier Transform (FFT) is critical in applications such as signal processing, communications, and AI. Embedded GPUs are often …
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SSFFT: Energy-Efficient Selective Scaling for Fast Fourier Transform in Embedded GPUs
Hierarchical Traversal Stack Design Using Shared Memory for GPU Ray Tracing
Ray tracing is widely used to generate photorealistic images by tracing the paths of light rays through a scene and their interactions …
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Hierarchical Traversal Stack Design Using Shared Memory for GPU Ray Tracing
Beyond VABlock: Improving Transformer Workloads through Aggressive Prefetching
The memory capacity constraint of GPUs is a major challenge in running large deep learning workloads with their ever increasing memory …
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Beyond VABlock: Improving Transformer Workloads through Aggressive Prefetching
VitBit: Enhancing Embedded GPU Performance for AI Workloads through Register Operand Packing
The rapid advancement of Artificial Intelligence (AI) necessitates significant enhancements in the energy efficiency of Graphics …
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VitBit: Enhancing Embedded GPU Performance for AI Workloads through Register Operand Packing
Performance Analysis of GEMV Kernels by GPU and PIM Memory Address Mapping Approaches
Processing-in-Memory(PIM)은 프로세서와 오프칩(off-chip) …
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Performance Analysis of GEMV Kernels by GPU and PIM Memory Address Mapping Approaches
Conflict-Aware Compiler for Hierarchical Register File on GPUs
Modern graphics processing units (GPUs) leverage a high degree of thread-level parallelism, necessitating large-sized register files …
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Conflict-Aware Compiler for Hierarchical Register File on GPUs
Adaptive Kernel Merge and Fusion for Multi-Tenant Inference in Embedded GPUs
This paper proposes a new scheme that improves throughput and reduces queuing delay while running multiple inferences in embedded …
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Adaptive Kernel Merge and Fusion for Multi-Tenant Inference in Embedded GPUs
Warped-MC: An Efficient Memory Controller Scheme for Massively Parallel Processors
The performance of GPU’s external memories is becoming more critical since a modern GPU runs thousands of concurrent threads that …
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Warped-MC: An Efficient Memory Controller Scheme for Massively Parallel Processors
Analyzing GCN Aggregation on GPU
Graph convolutional neural networks (GCNs) are emerging neural networks for graph structures that include large features associated …
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Analyzing GCN Aggregation on GPU