Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 116 for “"NVIDIA"”.
-
Performance Portability of CUDA Across NVIDIA GPU Architectures
… machine learning, simulations, and many others. NVIDIA GPUs currently outperform all of their competitors and thus make up the lion's share of today's market. Importantly, they are natively programmed using the proprietary framework Compute Unified Device Architecture (CUDA), which only compiles …
-
Performance Analysis and Optimization of Hermite Methods on NVIDIA GPUs Using CUDA
In this thesis we present the first, to our knowledge, implementation and performance analysis of Hermite methods on GPU accelerated systems. We give analytic background for Hermite methods; give implementations of the Hermite methods on traditional CPU systems as well as on GPUs; give the reader …
-
Real-Time Automatic Object Classification and Tracking using Genetic Programming and NVIDIA R CUDA TM
Genetic Programming (GP) is a widely used methodology for solving various computational problems. GP's problem solving ability is usually hindered by its long execution times. In this thesis, GP is applied toward real-time computer vision. In particular, object classification and tracking using a …
-
Architecture-Aware Mapping and Optimization on Heterogeneous Computing Systems
… popular GPU platforms, i.e., GPUs from AMD and NVIDIA. Optimization strategies for NVIDIA GPUs have been well studied but when applied on AMD GPUs, they fail to measurably improve performance because of the differences in underlying architecture. To the best of our knowledge, this research is …
-
Real-Time GPU Scheduling with Preemption Support for Autonomous Mobile Robots
… of these applications. We test our framework on NVIDIA AGX Xavier, which provides high computing power and supports eight different power modes. We measure the response times of all three applications with and without the scheduler on the NVIDIA AGX Xavier platform on different power modes, to …
-
Nyílt forrású tanítóarchitektúrák önvezető autókhoz
… kapjak a témáról. Ezek után tanulmányoztam az Nvidia Autopilot projektet és a Comma.ai 2016-os tanulmányát.
-
Understanding LLM Communictaion
… is a sequence alignment approach that correlates NVIDIA Collective Communications Library (NCCL) debug logs with NVIDIA Nsight Systems (Nsys) kernel traces, fusing semantic metadata with nanosecond-accurate timing without code instrumentation. The result- ing Python tool works with standard …
-
Time-Optimal Re-planning of Quadrotor Trajectories
… using a compiled real time inference library (NVIDIA TensorRT). The optimized planner is demonstrated to provide a 14.84 times increase in throughput and over 95% reduction in latency. The increase in throughput can be translated to better efficiency, and the reduction in latency is critical …
-
Exploiting Multigrain Parallelism in Pairwise Sequence Search on Emergent CMP Architectures
… multiple Cell Broadband Engines and within an nVIDIA GeForce General Purpose Graphics Processing Unit (GPGPU). Cell Broadband Engine: We parallelize the Smith-Waterman algorithm within a Cell node by performing a blocked data decomposition of the dynamic programming matrix followed by pipelined …
-
Acceleration of asymptotic computational electromagnetics physical optics — shooting and bouncing ray (PO-SBR) method using CUDA
… purpose graphics processing unit (GPGPU) using NVIDIA’s CUDA environment. In modern engineering, simulation programs are used to aid the development of advanced devices, and this is where CEM plays the important role of simulating the propagation of electromagnetic (EM) waves and fields using …
-
On the Complexity of Robust Source-to-Source Translation from CUDA to OpenCL
… Much of this growth has been driven by NVIDIA's CUDA ecosystem for developing GPGPU applications on NVIDIA hardware. However, with the increasing diversity of GPUs (including those from AMD, ARM, and Qualcomm), OpenCL has emerged as an open and vendor-agnostic environment for programming …
-
Delivering real-time holographic video content with off-the-shelf PC hardware
… Our system uses only 3 PCs each equipped with an nVidia Quadro FX 3000G video card. It replaces a SGI Onyx and the custom built Cheops Image Processing System that previously served as the platform driving the MIT second-generation Holovideo display. With a prototype content generation …
-
Toward predictable execution of real-time workloads on modern GPUs
… approaches to achieve predictable execution on NVIDIA GPUs. The first approach involves executing different tasks on disjoint sets of GPU processing units, that is, spatial partitioning (SP). There has been considerable effort by the industry and research community to enable GPU SP. However, …
-
Towards efficient, on-demand and automated deep learning
… The advanced and dedicated computing chips, like Nvidia GPU and Google TPU, largely contributed and broadened this success. However, the requirement of large computing power impedes the deployment of deep learning methods in many real scenarios, where cost, time and energy efficiency are critical …
-
Accelerating software radio astronomy FX correlation with GPU and FPGA co-processors
… 4LXlOO) and the other uses a graphics processor (Nvidia 9800GT). The objective of a radio astronomy correlator is to compute the complex valued correlation products for each baseline which can be used to reconstruct the sky's radio brightness distribution. Radio astronomy correlators have huge …
-
GPU-based digital hologram reconstruction and particle detection
… only special requirement being an off-the-shelf Nvidia GPU.
-
MLPerf PowerPack: Defining MLPerf Inference Benchmark's Power Profile
… specifically designed for AMD processors, and NVIDIA-SMI, a software power analysis tool developed for NVIDIA GPUs. The AC power draw of our system under test was measured using a HOBO Plug Load Data Logger to determine the energy consumption distribution among the CPU, GPU, and disk drive. Our …
-
TensorRT inference performance study in MLModelScope
… freezing and deploying the well-trained models, NVIDIA TensorRT is the leading framework that is exclusively developed for inference. It allows the developer to optimize the model to facilitate high-performance inference. While it has been shown extensively that TensorRT can significantly boost …
-
Applications of Riesz Transforms and Monogenic Wavelet Frames in Imaging and Image Processing
… der monogenen Wavelet Frames mit Hilfe des NVIDIA CUDA Frameworks vorzustellen. Bei einem empirischen Vergleich der vorgestellten Techniken mit den ursprünglichen Verfahren konnten präzisere Ergebnisse mit niedrigerer Rauschanfälligkeit nachgewiesen werden. Ein weiterer Punkt der Arbeit …
-
On Energy Modeling of Deep Neural Network Operations
… and predictor results. Profiling results of Nvidia A30 performance across several core clocks reveal an energy optimum of 900 MHz, aligning with the manufacturer base clock of 930 MHz. This work provides the tools which enable the correct choice of target GPU and clock speed for existing and …
Page 1 of 6