#gpuprogramming 搜索结果
🔥 New Series! Learning GPU programming through Mojo puzzles - on an Apple M4! No expensive data center GPUs needed. No CUDA C++ complexity. Just Python-like syntax with systems performance. First video just dropped: youtube.com/watch?v=-VsP4k… #Mojo #GPUProgramming #AppleSilicon
youtube.com
YouTube
Learn GPU Programming with Mojo 🔥 GPU Puzzles Tutorial - Introduction
Day 2 of #GPUProgramming: >read an article about shared memory >learnt about registers……..Global memory >almost blacked out from elaboration of L1 & L2 iykyk >”repetition”to digest what I just learnt for about 900k milliseconds
"Need better CUDA textbooks. 'Programming Massively Parallel Processors' is a good intro. I've created C/CUDA C implementations for first 3 chapters. Check book & my GitHub repo for details. #CUDA #GPUprogramming"
Each common operation is implemented as its own .cu file—modular. intriguing. #CUDA #NVIDIA #GPUProgramming #libcudf
"10 days into CUDA, and I’ve earned my first badge of honor! 🚀 From simple kernels to profiling, every day is a step closer to mastering GPU computing. Onward to 100! #CUDA #GPUProgramming #100DaysOfCUDA"
I started with @elliotarledge CUDA course, Here's the link youtu.be/86FAWCzIe_4?si… #gpu #gpuprogramming
youtube.com
YouTube
CUDA Programming Course – High-Performance Computing with GPUs
Day 3 of GPU programming At this rate I'll be writing custom inference kernels for AI by next month. The gap between PyTorch abstractions and bare metal isn't as wide as it seemed. #CUDA #GPUProgramming #MachineLearning
Day 2 of GPU programming Never knew addition needs so much code 😂 Starting to get the hang of program_id. Used Gemini 3.0 to generate pseudocode since I'm new to GPU programming and didn't want full code. Lets hope this momentum continues
Day 3 of #GPUProgramming: >in-depth of what shared memory is capable of >read about techniques by which these concepts optimize their performance >synchronization of threads during matmul >realized it took ~1.5 hours to digest this stuff >tried to code matrix multiplication…
#GPUProgramming - Day 07: 🔧 #CPU Hazards 101 🚧: Ever heard of #Register Renaming & Out-of-Order Execution? They tackle structural hazards, ensuring smooth sailing for instructions. Watch out for Data Hazards (#RAW, #WAR, #WAW) in #MIPS, but fear not! #COA #LearnInPublic
#GPUProgramming - Day 02: 🔄 Exploring CPU architectures! #RISC, like #ARM & #Power, opts for efficiency with many registers. #CISC, exemplified by #Intel 8086, prioritizes simplicity, offering diverse, complex instructions. RISC excels in energy efficiency. #COA #LearnInPublic
#GPUProgramming - Day 03: 🧠 CPUs: Processors adapt with DISA. #CPU's core duo - Control Unit & Datapath. Datapath: Registers, ALU, Buses, Multiplexers – a data symphony! 🔄 Follow the Instruction Execution Cycle: Fetch ➡️Decode➡️Execute➡️Store➡️ Update PC. 🕹️ #LearnInPublic
#GPUProgramming - Day 01: 🚀 Exploring RISC architecture: Simplified, optimized instructions in one clock cycle. 🔄 Bye, CISC complexity! 🏎️ Registers rule, boosting speed. 🤖💡 Compiler-friendly design, slick pipelining for simultaneous processing! 🕵️♂️ #COA #RISC #LearnInPublic
For maximum performance, firms often develop custom CUDA kernels. This involves writing low-level code to directly program the GPU's parallel cores, squeezing out every drop of efficiency for critical tasks. #CUDA #GPUProgramming
#GPUProgramming - Day 08: 🚀 Explored #computerarchitecture today! 🖥️ Control Hazards tackle branch prediction, #Pentium FDIV bug a classic example. 💡 Memory #Hierarchy is key—#RAM, #cache levels (L1, L2, L3), and storage devices play crucial roles. 🔄🌐 #Memory #LearnInPublic
#GPUProgramming - Day 04: 🕰️ Dive into processor architectures! 🧠 Single-cycle execution, one clock cycle per instruction, demands a versatile datapath. 🔄 Multi-cycle instructions break it down for a more intricate dance with time. ⏳ #ComputerArchitecture #LearnInPublic 🚀
#GPUProgramming - Day 06: 🔍 Diving into computer architecture! 🖥️ Structural hazards arise when hardware resources are in high demand, causing contention among instructions. Data hazards? RAW, WAR, WAW – the battle for data paths and registers! 💡 #COA #LearnInPublic
#GPUProgramming - Day 05: 🚀 Pipelining in computer architecture boosts performance by dividing instruction execution into stages. Techniques like forwarding, branch prediction, and superscalar processors enhance parallelism.💻🌐 #ComputerArchitecture #Pipelining #LearnInPublic
⚡ Built my own graphics engine: Asthrarisine Sounds fun? Reality = invisible meshes, memory bugs & shader headaches. But here’s what made it work: #OpenGL #GraphicsEngine #GPUProgramming #GLTF #GameDev #ShaderProgramming
Programming Tensor Cores in Unity with WMMA (Warp Matrix Multiply Accumulate) API. #gpuprogramming #unity3d I have written minimal example: github.com/przemyslawzawo…
🚀 Exciting Learning Opportunity! 🚀 For more details and registration: events.eurocc.lu/meluxina-intro… #GPUProgramming #CUDA #Supercomputing #ScientificComputing #MeluXina #Luxembourg
GPU PROGRAMMING PLAYLIST youtube.com/playlist?list=… #gpu #gpuprogramming #vulkan #vulkanapi #computergraphics #hpc #highperformancecomputing #nvidia #intel #amd #howtocode #howtoprogram #raytracing #dataviz #infographics #art #digitalart #artist #cudaeducation
GPU CODING PLAYLIST youtube.com/playlist?list=… #gpu #gpuprogramming #vulkan #vulkanapi #computergraphics #hpc #highperformancecomputing #nvidia #intel #amd #howtocode #howtoprogram #raytracing #dataviz #infographics #art #digitalart #artist #cudaeducation
COMPUTER GRAPHICS | Frustum culling equation to discard object that aren't relevant youtu.be/WmQPuaj_j4k #gpu #gpuprogramming #frustumculling #computergraphics #hpc #howtocode #howtoprogram #geometry #shader #intel #amd #nvidia #dataviz #computersimulation #cudaeducation
youtube.com
YouTube
Vulkan API Discussion | Frustrum Culling + Level of Detail + Indirect...
GPU CODING PLAYLIST youtube.com/playlist?list=… #gpu #gpuprogramming #vulkan #vulkanapi #computergraphics #hpc #highperformancecomputing #nvidia #intel #amd #howtocode #howtoprogram #raytracing #dataviz #infographics #art #digitalart #artist #cudaeducation
NSIGHT GRAPHICS TUTORIAL: youtu.be/LtretfoL2tc | Vulkan, OpenGL, Direct 3D profiling and debugging | #graphicsprogramming #gpuprogramming #gpgpu #howtoprogram #howtocode #computerprogramming #howtowriteaprogram #siliconvalley #cudaeducation
youtube.com
YouTube
Nsight Graphics Tutorial | Cuda Education
@nvidia GPU bootcamp in the Claustro of @URosario. @HPCCol growing stronger. #HPC #GPUProgramming #OpenACC
Day 5 of GPU Programming -matrix transpose. -matrix prefix sum leetcode. #100DaysOfGPU #CUDA #GPUProgramming #ParallelComputing #AI #DeepLearning #100DaysOfCode #MachineLearning #NVIDIA #CodingJourney
Day 8 of GPU Programming -Count 2D Array Element -todays potd easy peasy again. #100DaysOfGPU #CUDA #GPUProgramming #ParallelComputing #AI #DeepLearning #100DaysOfCode #MachineLearning #NVIDIA #CodingJourney
Day 3 of GPU Programming -implemented ReLU activation for 1D array -Did potd leetcod -explored how GPUs handle element-wise operations in parallel #100DaysOfGPU #CUDA #GPUProgramming #ParallelComputing #AI #DeepLearning #100DaysOfCode #MachineLearning #NVIDIA #CodingJourney
Day 9 of GPU Programming -Leaky ReLU -leetcode potd easy but hard to implement #100DaysOfGPU #CUDA #GPUProgramming #ParallelComputing #AI #DeepLearning #100DaysOfCode #MachineLearning #NVIDIA #CodingJourney
Compilation errors when using OpenACC with g++ 10 stackoverflow.com/questions/6542… #openacc #gpuprogramming #g++ #compilererrors #cpp
Day 7 of GPU Programming -color inversion. -todays potd easy peasy. #100DaysOfGPU #CUDA #GPUProgramming #ParallelComputing #AI #DeepLearning #100DaysOfCode #MachineLearning #NVIDIA #CodingJourney
Day 10 of GPU Programming - Rainbow Table - 4th consecutive easy problem on LeetCode #100DaysOfGPU #CUDA #GPUProgramming #ParallelComputing #AI #DeepLearning #100DaysOfCode #MachineLearning #NVIDIA #CodingJourney pic.x.com/FYOUlLsQy3
Day 6 of GPU Programming -matrix addition. -todays potd was on harder side. #100DaysOfGPU #CUDA #GPUProgramming #ParallelComputing #AI #DeepLearning #100DaysOfCode #MachineLearning #NVIDIA #CodingJourney pic.x.com/9qrJliv3Fdhttp…
Day 3 of GPU programming At this rate I'll be writing custom inference kernels for AI by next month. The gap between PyTorch abstractions and bare metal isn't as wide as it seemed. #CUDA #GPUProgramming #MachineLearning
Day 2 of GPU programming Never knew addition needs so much code 😂 Starting to get the hang of program_id. Used Gemini 3.0 to generate pseudocode since I'm new to GPU programming and didn't want full code. Lets hope this momentum continues
Day 2 of #GPUProgramming: >read an article about shared memory >learnt about registers……..Global memory >almost blacked out from elaboration of L1 & L2 iykyk >”repetition”to digest what I just learnt for about 900k milliseconds
"Need better CUDA textbooks. 'Programming Massively Parallel Processors' is a good intro. I've created C/CUDA C implementations for first 3 chapters. Check book & my GitHub repo for details. #CUDA #GPUprogramming"
NSIGHT GRAPHICS TUTORIAL: amzn.to/2Qffvpl | Vulkan, OpenGL, Direct 3D profiling and debugging | #graphicsprogramming #gpuprogramming #gpgpu #howtoprogram #howtocode #computerprogramming #howtowriteaprogram #siliconvalley #nsightgraphicstutorial #videowalkthrough
Each common operation is implemented as its own .cu file—modular. intriguing. #CUDA #NVIDIA #GPUProgramming #libcudf
#GPUProgramming - Day 07: 🔧 #CPU Hazards 101 🚧: Ever heard of #Register Renaming & Out-of-Order Execution? They tackle structural hazards, ensuring smooth sailing for instructions. Watch out for Data Hazards (#RAW, #WAR, #WAW) in #MIPS, but fear not! #COA #LearnInPublic
#GPUProgramming - Day 02: 🔄 Exploring CPU architectures! #RISC, like #ARM & #Power, opts for efficiency with many registers. #CISC, exemplified by #Intel 8086, prioritizes simplicity, offering diverse, complex instructions. RISC excels in energy efficiency. #COA #LearnInPublic
#GPUProgramming - Day 03: 🧠 CPUs: Processors adapt with DISA. #CPU's core duo - Control Unit & Datapath. Datapath: Registers, ALU, Buses, Multiplexers – a data symphony! 🔄 Follow the Instruction Execution Cycle: Fetch ➡️Decode➡️Execute➡️Store➡️ Update PC. 🕹️ #LearnInPublic
#GPUProgramming - Day 01: 🚀 Exploring RISC architecture: Simplified, optimized instructions in one clock cycle. 🔄 Bye, CISC complexity! 🏎️ Registers rule, boosting speed. 🤖💡 Compiler-friendly design, slick pipelining for simultaneous processing! 🕵️♂️ #COA #RISC #LearnInPublic
#GPUProgramming - Day 08: 🚀 Explored #computerarchitecture today! 🖥️ Control Hazards tackle branch prediction, #Pentium FDIV bug a classic example. 💡 Memory #Hierarchy is key—#RAM, #cache levels (L1, L2, L3), and storage devices play crucial roles. 🔄🌐 #Memory #LearnInPublic
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