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Dell NVIDIA Tesla V100S 32 GB, 260W, Double Wide, Passive, Full Height GPU, Customer Install

Dell NVIDIA Tesla V100S 32 GB, 260W, Double Wide, Passive, Full Height GPU, Customer Install

Accelerate your most demanding HPC, hyperscale, and enterprise data center workloads with NVIDIA® Tesla® GPU accelerators. Scientists can now crunch through petabytes of data faster than with CPUs in applications ranging from energy exploration to deep learning. Plus, Tesla accelerators deliver the horsepower needed to run bigger simulations faster than ever before. For enterprises deploying VDI, Tesla accelerators are perfect for accelerating virtual desktops to any user, anywhere.

GBP 18745.19
1

GPU Parallel Program Development Using CUDA

GPU Parallel Program Development Using CUDA

GPU Parallel Program Development using CUDA teaches GPU programming by showing the differences among different families of GPUs. This approach prepares the reader for the next generation and future generations of GPUs. The book emphasizes concepts that will remain relevant for a long time rather than concepts that are platform-specific. At the same time the book also provides platform-dependent explanations that are as valuable as generalized GPU concepts. The book consists of three separate parts; it starts by explaining parallelism using CPU multi-threading in Part I. A few simple programs are used to demonstrate the concept of dividing a large task into multiple parallel sub-tasks and mapping them to CPU threads. Multiple ways of parallelizing the same task are analyzed and their pros/cons are studied in terms of both core and memory operation. Part II of the book introduces GPU massive parallelism. The same programs are parallelized on multiple Nvidia GPU platforms and the same performance analysis is repeated. Because the core and memory structures of CPUs and GPUs are different the results differ in interesting ways. The end goal is to make programmers aware of all the good ideas as well as the bad ideas so readers can apply the good ideas and avoid the bad ideas in their own programs. Part III of the book provides pointer for readers who want to expand their horizons. It provides a brief introduction to popular CUDA libraries (such as cuBLAS cuFFT NPP and Thrust) the OpenCL programming language an overview of GPU programming using other programming languages and API libraries (such as Python OpenCV OpenGL and Apple’s Swift and Metal ) and the deep learning library cuDNN.

GBP 44.99
1

Dell 32GB NVIDIA Tesla M10 Graphic Card

Dell 32GB NVIDIA Tesla M10 Graphic Card

Accelerate your most demanding HPC, hyperscale, and enterprise data center workloads with NVIDIA® Tesla® GPU accelerators. Scientists can now crunch through petabytes of data faster than with CPUs in applications ranging from energy exploration to deep learning. Plus, Tesla accelerators deliver the horsepower needed to run bigger simulations faster than ever before. For enterprises deploying VDI, Tesla accelerators are perfect for accelerating virtual desktops to any user, anywhere.

GBP 3619.28
1