tt-awesome — Articles & Resources Articles, papers, lessons, talks, videos, and demos from the Tenstorrent ecosystem https://tenstorrent.github.io/tt-awesome/feeds/articles.xml Tenstorrent Communityhttps://tenstorrent.github.io/tt-awesome/ 2026-08-10T23:59:59Z https://github.com/prag79/tt-sim-lab/blob/main/HANDOUT.md tt-sim Lab — Student handout 2026-08-10T23:59:59Z A university teaching lab for TT-Metalium kernel programming on a virtual Tenstorrent chip — one-click GitHub Codespace, no silicon and nothing installed locally. The primary track (labs 00-06) points tt-metal straight at libttsim via TT_METAL_SIMULATOR and walks from elementwise add through NoC multicast to multi-core and multicast matmul, backed by a source-level matmul guide. An optional advanced track (labs 10-16) boots an Ubuntu guest under ttsim-qemu, loads tt-kmd, surfaces /dev/tenstorrent/0, and runs tt-metal through the full PCIe path.

Links: Repo · Student handout · Matmul source walkthrough

By @Pragnajit Datta Roy · affiliated · added 2026-08-10

ttsim, simulator, qemu, codespaces, metalium, matmul, labs, curriculum, academia, education, guides, kernels, getting-started

]]> https://github.com/prag79/tt-sim-lab/blob/main/labs/MATMUL_GUIDE.md tt-sim Lab — Matmul source walkthrough 2026-08-10T23:59:58Z A university teaching lab for TT-Metalium kernel programming on a virtual Tenstorrent chip — one-click GitHub Codespace, no silicon and nothing installed locally. The primary track (labs 00-06) points tt-metal straight at libttsim via TT_METAL_SIMULATOR and walks from elementwise add through NoC multicast to multi-core and multicast matmul, backed by a source-level matmul guide. An optional advanced track (labs 10-16) boots an Ubuntu guest under ttsim-qemu, loads tt-kmd, surfaces /dev/tenstorrent/0, and runs tt-metal through the full PCIe path.

Links: Repo · Student handout · Matmul source walkthrough

By @Pragnajit Datta Roy · affiliated · added 2026-08-10

ttsim, simulator, qemu, codespaces, metalium, matmul, labs, curriculum, academia, education, guides, kernels, getting-started

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/animatediff-video-generation/ tt-animatediff — Native Video Animation with AnimateDiff (VSCode Toolkit) 2026-06-03T23:59:57Z Generates short, temporally coherent animated GIFs using the AnimateDiff model on Tenstorrent hardware. Phase 1 runs the correct SD 1.4 + MotionAdapter architecture on CPU; Phase 2 accelerates spatial denoising on Blackhole using the TTNN UNet. Produces vibrant 8-frame animations in ~15 s/frame on a P300C.

Links: Repo · Native Video Animation with AnimateDiff (VSCode Toolkit)

official · added 2026-06-03

animatediff, video-generation, stable-diffusion, diffusion, gif, blackhole, ai-models, games-demos

]]> https://github.com/tenstorrent/tt-llk/blob/main/docs/llk/l2/top_level_overview.md tt-llk — Top-level architecture overview 2026-05-13T23:59:56Z Tenstorrent Low-Level Kernels: the C++ library that directly programs the RISC-V cores inside each Tensix compute engine. TRISC0 (unpack), TRISC1 (math/FPU/SFPU), and TRISC2 (pack) are all programmed through this layer — it is the interface between TT-Metal kernel code and bare silicon.

Links: Repo · Top-level architecture overview

official · added 2026-05-13

tensix, risc-v, llk, trisc, brisc, ncrisc, low-level, compute-engine, kernels, riscv-arch

]]> https://www.youtube.com/watch?v=CixEFPc8oxg Tenstorrent Architecture — W&M CSCI654 Advanced Computer Architecture — Lecture 20 — Tenstorrent Architecture (YouTube) 2026-05-13T23:59:55Z Lecture 20 from William & Mary's graduate Computer Architecture course. Frames Tenstorrent in the landscape between GPUs and TPUs, draws comparisons to Cerebras and SambaNova, then dives deep into the Wormhole chip and Tensix core: the 5 RISC-V core design, SFPU, NoC, and dataflow execution model.

Links: Lecture 20 — Tenstorrent Architecture (YouTube)

By Yifan & GPU / William & Mary · community · added 2026-05-13

lecture, architecture, wormhole, tensix, risc-v, sfpu, noc, academia, guides, riscv-arch

]]> https://arxiv.org/abs/2407.13885 Attention in SRAM on Tenstorrent Grayskull — arXiv:2407.13885 2026-05-13T23:59:54Z A fused kernel for the Grayskull architecture implementing Transformer self-attention entirely within SRAM. Combines matrix multiply, attention score scaling, and Softmax without DRAM accesses, achieving significant speedups over non-fused implementations.

Links: arXiv:2407.13885

By Moritz Thüning · community · added 2026-05-13

attention, transformer, sram, grayskull, kernel, risc-v, research, kernels

]]> https://arxiv.org/abs/2505.06085 Assessing Tenstorrent Grayskull RISC-V MatMul Acceleration for LLMs — arXiv:2505.06085 2026-05-13T23:59:53Z Evaluates the Tenstorrent Grayskull e75 RISC-V accelerator for matrix multiplication at reduced numerical precision (BFP8 and LoFi), a fundamental kernel in LLM inference computation.

Links: arXiv:2505.06085

By Hiari Pizzini Cavagna, Daniele Cesarini, Andrea Bartolini · community · added 2026-05-13

matmul, grayskull, risc-v, bfp8, lofi, llm, precision, research

]]> https://arxiv.org/abs/2605.02744 Porting Strategies for Gravitational N-Body Simulations on Tenstorrent Wormhole — arXiv:2605.02744 2026-05-13T23:59:52Z Evaluates three strategies for scaling an N-body code across multiple Tenstorrent Wormhole accelerators. Builds on the established performance of single-card N-body work to explore parallelism via the on-chip NoC and multi-accelerator configurations.

Links: arXiv:2605.02744

By Jenny Lynn Almerol, Elisabetta Boella, Mario Spera, Daniele Gregori · community · added 2026-05-13

n-body, astrophysics, hpc, wormhole, risc-v, multi-accelerator, simulation, research

]]> https://arxiv.org/abs/2512.22168 TileLoom: Automatic Dataflow Planning for Spatial Dataflow Accelerators — arXiv:2512.22168 2026-05-13T23:59:51Z Compiler system that automatically generates efficient dataflow plans for tile-based languages on spatial accelerators including Tenstorrent Wormhole. Exploits on-chip network forwarding between processing elements to reduce DRAM pressure.

Links: arXiv:2512.22168

By Wei Li, Zhenyu Bai, Heru Wang, Pranav Dangi · community · added 2026-05-13

compiler, dataflow, spatial-accelerator, tile-based, on-chip-network, wormhole, research, compilers

]]> https://arxiv.org/abs/2604.03279 Rewriting TTS Inference Economics: Lightning V2 on Tenstorrent vs. NVIDIA L40S — arXiv:2604.03279 2026-05-13T23:59:50Z Shows that Text-to-Speech inference on Tenstorrent Lightning V2 achieves 4× lower cost than NVIDIA L40S. Applies BlockFloat8 (BFP8) and low-fidelity (LoFi) precision strategies to TTS despite their greater numerical fragility compared to LLMs.

Links: arXiv:2604.03279

By Ranjith M. S., Akshat Mandloi, Sudarshan Kamath · community · added 2026-05-13

tts, text-to-speech, inference, bfp8, lofi, cost-efficiency, precision, research, ai-models

]]> https://anuraagw.me/blog/blackhole-architecture Tenstorrent Blackhole Architecture Guide — anuraagw.me — February 2026 2026-05-13T23:59:49Z A 6,500-word community deep dive into the Blackhole p100a architecture: the tile model (Tensix, DRAM, SiFive x280 L2CPU, Ethernet, PCIe, NoC arc), firmware startup sequence, MOP micro-op processor, replay buffer, FPU/SFPU sync, and the anatomy of a kernel. From the author of blackhole-py.

Links: anuraagw.me — February 2026

By boopdotpng · community · added 2026-05-13

blackhole, architecture, tensix, noc, sifive-x280, firmware, mop, sfpu, deep-dive, blog, riscv-arch, guides, blogs

]]> https://arxiv.org/abs/2605.07599 Stencil Computations on Tenstorrent Wormhole — arXiv:2605.07599 2026-05-12T23:59:48Z Maps 2D 5-point stencil computations onto the Tenstorrent Wormhole RISC-V AI dataflow accelerator via two implementations: element-wise decomposition (Axpy) and matrix-multiplication reformulation (MatMul). Profiling shows the isolated Wormhole kernel is competitive with CPU execution, with PCIe transfers and initialization driving end-to-end overhead; Axpy achieves lower energy than the CPU baseline at large scales. Identifies architectural and software directions for making AI accelerators viable for HPC stencil workloads. 2025.

Links: arXiv:2605.07599

community · added 2026-05-12

stencil, hpc, wormhole, risc-v, energy-efficiency, benchmarks, dataflow, research

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/ttsim-twenty-and-ten/ ttsim — Lesson 2026-05-08T23:59:47Z Fast full-system simulator of Tenstorrent Wormhole and Blackhole hardware. Runs TT-Metalium workloads on any Linux/x86_64 system without physical silicon. Bit-exact results relative to hardware.

Links: Repo · Lesson

official · added 2026-05-08

simulator, no-hardware, bit-exact, wormhole, blackhole, riscv-arch, dev-tools

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/tt-xla-jax/ tt-xla — JAX and PyTorch/XLA on Tenstorrent 2026-05-08T23:59:46Z PJRT device plugin for Tenstorrent hardware. Enables JAX, PyTorch/XLA, and other XLA-based frameworks to target TT accelerators.

Links: Repo · JAX and PyTorch/XLA on Tenstorrent · Website

official · added 2026-05-08

xla, pjrt, jax, pytorch, compilers

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/tt-inference-server-lesson/ tt-inference-server — Production Inference lesson (VSCode Toolkit) 2026-05-08T23:59:45Z Production-ready model serving for Tenstorrent hardware with OpenAI-compatible REST API. Supports continuous batching, multiple models, and all TT hardware configurations.

Links: Repo · Production Inference lesson (VSCode Toolkit)

official · added 2026-05-08

serving, openai-compatible, production, rest-api, ai-models, cloud-infra, getting-started

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/tt-lang-intro/ tt-lang — Introduction to tt-lang 2026-05-08T23:59:44Z Python-based DSL that sits between TT-NN and TT-Metalium — expresses custom fused kernels with progressive disclosure, compiling directly to Tensix. Ships an integrated functional simulator (no hardware needed), line-by-line performance metrics, and AI-agent-friendly tooling. Two packages: tt-lang (compiler + hardware, requires ttnn) and tt-lang-sim (simulator only, works on Linux/macOS without Tenstorrent hardware).

Links: Repo · Website · Introduction to tt-lang

official · added 2026-05-08

dsl, python, kernels, tt-lang, simulator, kernel-fusion, kernels, getting-started

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/modern-setup/ tt-installer — Modern Setup lesson (VSCode Toolkit) 2026-05-08T23:59:43Z Install the complete Tenstorrent software stack with one command. Handles drivers, firmware, Python environment, and SDK setup automatically.

Links: Repo · Modern Setup lesson (VSCode Toolkit)

official · added 2026-05-08

installation, setup, one-command, getting-started, hw-system, guides, getting-started

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons tt-vscode-toolkit — All 48 lessons 2026-05-08T23:59:42Z 48 interactive lessons covering the full Tenstorrent developer path — from hardware detection to custom training — with click-to-run commands and hardware auto-detection. Available in VSCode and code-server.

Links: Repo · All 48 lessons · RISC-V Programming Guide

official · added 2026-05-08

vscode, lessons, interactive, getting-started, code-server, guides, dev-tools, getting-started

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/riscv-guide/ tt-vscode-toolkit — RISC-V Programming Guide 2026-05-08T23:59:41Z 48 interactive lessons covering the full Tenstorrent developer path — from hardware detection to custom training — with click-to-run commands and hardware auto-detection. Available in VSCode and code-server.

Links: Repo · All 48 lessons · RISC-V Programming Guide

official · added 2026-05-08

vscode, lessons, interactive, getting-started, code-server, guides, dev-tools, getting-started

]]> https://fosdem.org/2026/schedule/event/AJLNVH-tt-boltz/ tt-bio — FOSDEM 2026 — Drug Discovery on Tenstorrent Hardware 2026-05-08T23:59:40Z Boltz-2 biomolecular model for drug discovery on Tenstorrent Blackhole. Supports single-card and multi-card configurations — QuietBox (4×) and Galaxy (32×). Approaches physics-based FEP accuracy at 1000× the speed.

Links: Repo · FOSDEM 2026 — Drug Discovery on Tenstorrent Hardware

By @moritztng · affiliated · added 2026-05-08

drug-discovery, blackhole, inference, biology, multi-card, ai-models, research

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/qb2-openclaw-assistant/ tt-claw — OpenClaw AI Assistant on QuietBox 2 2026-05-08T23:59:39Z A Tenstorrent-powered claw machine that rewards players with real prizes. The QuietBox 2 runs local AI inference to act as an agent controlling the claw hardware — the OpenClaw AI assistant lesson builds directly on this project.

Links: Repo · OpenClaw AI Assistant on QuietBox 2

By @tsingletaryTT · affiliated · added 2026-05-08

claw-machine, agents, hardware, quietbox, physical, on-device, agents, games-demos

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/qb2-local-agents/ Local AI Agents on Tenstorrent — Local AI Agents on QuietBox 2 2026-05-08T23:59:38Z Three agentic projects running fully on-device: local AI agents on QuietBox 2, a coding assistant powered by Aider against a local inference server, and the OpenClaw AI assistant on QuietBox 2. No cloud APIs — all inference runs on TT hardware.

Links: Local AI Agents on QuietBox 2 · Coding Assistant with Aider

By tsingletaryTT · affiliated · added 2026-05-08

agents, local-llm, aider, coding-assistant, quietbox, on-device, agents

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/coding-assistant/ Local AI Agents on Tenstorrent — Coding Assistant with Aider 2026-05-08T23:59:37Z Three agentic projects running fully on-device: local AI agents on QuietBox 2, a coding assistant powered by Aider against a local inference server, and the OpenClaw AI assistant on QuietBox 2. No cloud APIs — all inference runs on TT hardware.

Links: Local AI Agents on QuietBox 2 · Coding Assistant with Aider

By tsingletaryTT · affiliated · added 2026-05-08

agents, local-llm, aider, coding-assistant, quietbox, on-device, agents

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/image-generation/ Stable Diffusion XL on Tenstorrent — Image Generation with Stable Diffusion XL 2026-05-08T23:59:36Z On-device image generation with Stable Diffusion XL running entirely on Tenstorrent hardware. Full inference pipeline with no cloud dependency.

Links: Image Generation with Stable Diffusion XL

By tsingletaryTT · affiliated · added 2026-05-08

stable-diffusion, sdxl, image-generation, diffusion, on-device, ai-models

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/video-generation-ttmetal/ Video Generation on Tenstorrent — Video Generation via Frame-by-Frame Diffusion 2026-05-08T23:59:35Z Three lesson-projects covering on-device video synthesis: frame-by-frame diffusion with tt-local-generator, native AnimateDiff video animation, and video generation on QuietBox 2. All run entirely on TT hardware with no cloud dependency.

Links: Video Generation via Frame-by-Frame Diffusion · Native Video Animation with AnimateDiff · Video Generation on QuietBox 2

By tsingletaryTT · affiliated · added 2026-05-08

video-generation, diffusion, animatediff, tt-local-generator, quietbox, on-device, ai-models

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/qb2-video-generation/ Video Generation on Tenstorrent — Video Generation on QuietBox 2 2026-05-08T23:59:34Z Three lesson-projects covering on-device video synthesis: frame-by-frame diffusion with tt-local-generator, native AnimateDiff video animation, and video generation on QuietBox 2. All run entirely on TT hardware with no cloud dependency.

Links: Video Generation via Frame-by-Frame Diffusion · Native Video Animation with AnimateDiff · Video Generation on QuietBox 2

By tsingletaryTT · affiliated · added 2026-05-08

video-generation, diffusion, animatediff, tt-local-generator, quietbox, on-device, ai-models

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/forge-image-classification/ Image Classification with TT-Forge — Image Classification with TT-Forge 2026-05-08T23:59:33Z End-to-end image classification project using TT-Forge — compile and run a PyTorch classification model on Tenstorrent hardware with no kernel authoring required.

Links: Image Classification with TT-Forge

By tsingletaryTT · affiliated · added 2026-05-08

forge, image-classification, pytorch, compiler, inference, compilers, ai-models

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/tensix-playground/ Tensix Grid Playground — Tensix Grid Playground (interactive) 2026-05-08T23:59:32Z Interactive browser-based visualizer of the Tenstorrent Tensix grid architecture. Explore the NoC, core layout, and dataflow patterns without hardware — a great companion for learning kernel programming.

Links: Tensix Grid Playground (interactive)

By tsingletaryTT · affiliated · added 2026-05-08

visualization, interactive, noc, tensix, browser, architecture, dev-tools, riscv-arch

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/cookbook-game-of-life/ Tenstorrent Cookbook: Conway's Game of Life — Cookbook Recipe 1: Conway's Game of Life 2026-05-08T23:59:31Z TT-Metalium implementation of Conway's Game of Life as a cookbook recipe. Each generation is a full parallel kernel dispatch over the grid — a clean introduction to stateful compute on Tensix cores.

Links: Cookbook Recipe 1: Conway's Game of Life

By tsingletaryTT · affiliated · added 2026-05-08

game-of-life, demo, cookbook, parallel, metalium, games-demos, kernels

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/cookbook-particle-life/ Tenstorrent Cookbook: Particle Life Simulator — Cookbook Recipe 5: Particle Life Simulator 2026-05-08T23:59:30Z Particle Life simulation on Tenstorrent hardware — an emergent-behavior N-body system where simple attraction/repulsion rules between species produce complex lifelike patterns. Cookbook recipe demonstrating parallel N-body compute on Tensix.

Links: Cookbook Recipe 5: Particle Life Simulator

By tsingletaryTT · affiliated · added 2026-05-08

particle-life, n-body, simulation, emergent, cookbook, demo, games-demos, kernels

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/cs-fundamentals-01-computer/ CS Fundamentals on Tenstorrent Hardware — Module 1: RISC-V & Computer Architecture 2026-05-08T23:59:29Z Seven-module computer science curriculum taught on real Tenstorrent hardware. Covers RISC-V architecture, memory hierarchy, parallel computing, networks and NoC, synchronization, abstraction layers, and computational complexity — all grounded in what is physically happening on the chip.

Links: Module 1: RISC-V & Computer Architecture · Module 2: The Memory Hierarchy · Module 3: Parallel Computing · Module 4: Networks and Communication · Module 5: Synchronization · Module 6: Abstraction Layers · Module 7: Computational Complexity in Practice

By tsingletaryTT · affiliated · added 2026-05-08

computer-science, curriculum, risc-v, parallelism, memory, noc, education, guides, riscv-arch

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/cs-fundamentals-02-memory/ CS Fundamentals on Tenstorrent Hardware — Module 2: The Memory Hierarchy 2026-05-08T23:59:28Z Seven-module computer science curriculum taught on real Tenstorrent hardware. Covers RISC-V architecture, memory hierarchy, parallel computing, networks and NoC, synchronization, abstraction layers, and computational complexity — all grounded in what is physically happening on the chip.

Links: Module 1: RISC-V & Computer Architecture · Module 2: The Memory Hierarchy · Module 3: Parallel Computing · Module 4: Networks and Communication · Module 5: Synchronization · Module 6: Abstraction Layers · Module 7: Computational Complexity in Practice

By tsingletaryTT · affiliated · added 2026-05-08

computer-science, curriculum, risc-v, parallelism, memory, noc, education, guides, riscv-arch

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/cs-fundamentals-03-parallelism/ CS Fundamentals on Tenstorrent Hardware — Module 3: Parallel Computing 2026-05-08T23:59:27Z Seven-module computer science curriculum taught on real Tenstorrent hardware. Covers RISC-V architecture, memory hierarchy, parallel computing, networks and NoC, synchronization, abstraction layers, and computational complexity — all grounded in what is physically happening on the chip.

Links: Module 1: RISC-V & Computer Architecture · Module 2: The Memory Hierarchy · Module 3: Parallel Computing · Module 4: Networks and Communication · Module 5: Synchronization · Module 6: Abstraction Layers · Module 7: Computational Complexity in Practice

By tsingletaryTT · affiliated · added 2026-05-08

computer-science, curriculum, risc-v, parallelism, memory, noc, education, guides, riscv-arch

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/cs-fundamentals-04-networks/ CS Fundamentals on Tenstorrent Hardware — Module 4: Networks and Communication 2026-05-08T23:59:26Z Seven-module computer science curriculum taught on real Tenstorrent hardware. Covers RISC-V architecture, memory hierarchy, parallel computing, networks and NoC, synchronization, abstraction layers, and computational complexity — all grounded in what is physically happening on the chip.

Links: Module 1: RISC-V & Computer Architecture · Module 2: The Memory Hierarchy · Module 3: Parallel Computing · Module 4: Networks and Communication · Module 5: Synchronization · Module 6: Abstraction Layers · Module 7: Computational Complexity in Practice

By tsingletaryTT · affiliated · added 2026-05-08

computer-science, curriculum, risc-v, parallelism, memory, noc, education, guides, riscv-arch

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/cs-fundamentals-05-synchronization/ CS Fundamentals on Tenstorrent Hardware — Module 5: Synchronization 2026-05-08T23:59:25Z Seven-module computer science curriculum taught on real Tenstorrent hardware. Covers RISC-V architecture, memory hierarchy, parallel computing, networks and NoC, synchronization, abstraction layers, and computational complexity — all grounded in what is physically happening on the chip.

Links: Module 1: RISC-V & Computer Architecture · Module 2: The Memory Hierarchy · Module 3: Parallel Computing · Module 4: Networks and Communication · Module 5: Synchronization · Module 6: Abstraction Layers · Module 7: Computational Complexity in Practice

By tsingletaryTT · affiliated · added 2026-05-08

computer-science, curriculum, risc-v, parallelism, memory, noc, education, guides, riscv-arch

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/cs-fundamentals-06-abstraction/ CS Fundamentals on Tenstorrent Hardware — Module 6: Abstraction Layers 2026-05-08T23:59:24Z Seven-module computer science curriculum taught on real Tenstorrent hardware. Covers RISC-V architecture, memory hierarchy, parallel computing, networks and NoC, synchronization, abstraction layers, and computational complexity — all grounded in what is physically happening on the chip.

Links: Module 1: RISC-V & Computer Architecture · Module 2: The Memory Hierarchy · Module 3: Parallel Computing · Module 4: Networks and Communication · Module 5: Synchronization · Module 6: Abstraction Layers · Module 7: Computational Complexity in Practice

By tsingletaryTT · affiliated · added 2026-05-08

computer-science, curriculum, risc-v, parallelism, memory, noc, education, guides, riscv-arch

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/cs-fundamentals-07-complexity/ CS Fundamentals on Tenstorrent Hardware — Module 7: Computational Complexity in Practice 2026-05-08T23:59:23Z Seven-module computer science curriculum taught on real Tenstorrent hardware. Covers RISC-V architecture, memory hierarchy, parallel computing, networks and NoC, synchronization, abstraction layers, and computational complexity — all grounded in what is physically happening on the chip.

Links: Module 1: RISC-V & Computer Architecture · Module 2: The Memory Hierarchy · Module 3: Parallel Computing · Module 4: Networks and Communication · Module 5: Synchronization · Module 6: Abstraction Layers · Module 7: Computational Complexity in Practice

By tsingletaryTT · affiliated · added 2026-05-08

computer-science, curriculum, risc-v, parallelism, memory, noc, education, guides, riscv-arch

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/ct1-understanding-training/ Custom Model Training on Tenstorrent — Understanding Custom Training 2026-05-08T23:59:22Z Eight-lesson series covering the full custom training workflow on TT hardware: dataset fundamentals, configuration patterns, fine-tuning, multi-device distributed training, experiment tracking, model architecture basics, and training from scratch.

Links: Understanding Custom Training · Dataset Fundamentals · Configuration Patterns · Fine-tuning Basics · Multi-Device Training · Experiment Tracking · Model Architecture Basics · Training from Scratch

By tsingletaryTT · affiliated · added 2026-05-08

training, fine-tuning, multi-device, distributed, experiment-tracking, curriculum, guides, ai-models

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/ct2-dataset-fundamentals/ Custom Model Training on Tenstorrent — Dataset Fundamentals 2026-05-08T23:59:21Z Eight-lesson series covering the full custom training workflow on TT hardware: dataset fundamentals, configuration patterns, fine-tuning, multi-device distributed training, experiment tracking, model architecture basics, and training from scratch.

Links: Understanding Custom Training · Dataset Fundamentals · Configuration Patterns · Fine-tuning Basics · Multi-Device Training · Experiment Tracking · Model Architecture Basics · Training from Scratch

By tsingletaryTT · affiliated · added 2026-05-08

training, fine-tuning, multi-device, distributed, experiment-tracking, curriculum, guides, ai-models

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/ct3-configuration-patterns/ Custom Model Training on Tenstorrent — Configuration Patterns 2026-05-08T23:59:20Z Eight-lesson series covering the full custom training workflow on TT hardware: dataset fundamentals, configuration patterns, fine-tuning, multi-device distributed training, experiment tracking, model architecture basics, and training from scratch.

Links: Understanding Custom Training · Dataset Fundamentals · Configuration Patterns · Fine-tuning Basics · Multi-Device Training · Experiment Tracking · Model Architecture Basics · Training from Scratch

By tsingletaryTT · affiliated · added 2026-05-08

training, fine-tuning, multi-device, distributed, experiment-tracking, curriculum, guides, ai-models

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/ct4-finetuning-basics/ Custom Model Training on Tenstorrent — Fine-tuning Basics 2026-05-08T23:59:19Z Eight-lesson series covering the full custom training workflow on TT hardware: dataset fundamentals, configuration patterns, fine-tuning, multi-device distributed training, experiment tracking, model architecture basics, and training from scratch.

Links: Understanding Custom Training · Dataset Fundamentals · Configuration Patterns · Fine-tuning Basics · Multi-Device Training · Experiment Tracking · Model Architecture Basics · Training from Scratch

By tsingletaryTT · affiliated · added 2026-05-08

training, fine-tuning, multi-device, distributed, experiment-tracking, curriculum, guides, ai-models

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/ct5-multi-device-training/ Custom Model Training on Tenstorrent — Multi-Device Training 2026-05-08T23:59:18Z Eight-lesson series covering the full custom training workflow on TT hardware: dataset fundamentals, configuration patterns, fine-tuning, multi-device distributed training, experiment tracking, model architecture basics, and training from scratch.

Links: Understanding Custom Training · Dataset Fundamentals · Configuration Patterns · Fine-tuning Basics · Multi-Device Training · Experiment Tracking · Model Architecture Basics · Training from Scratch

By tsingletaryTT · affiliated · added 2026-05-08

training, fine-tuning, multi-device, distributed, experiment-tracking, curriculum, guides, ai-models

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/ct6-experiment-tracking/ Custom Model Training on Tenstorrent — Experiment Tracking 2026-05-08T23:59:17Z Eight-lesson series covering the full custom training workflow on TT hardware: dataset fundamentals, configuration patterns, fine-tuning, multi-device distributed training, experiment tracking, model architecture basics, and training from scratch.

Links: Understanding Custom Training · Dataset Fundamentals · Configuration Patterns · Fine-tuning Basics · Multi-Device Training · Experiment Tracking · Model Architecture Basics · Training from Scratch

By tsingletaryTT · affiliated · added 2026-05-08

training, fine-tuning, multi-device, distributed, experiment-tracking, curriculum, guides, ai-models

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/ct7-architecture-basics/ Custom Model Training on Tenstorrent — Model Architecture Basics 2026-05-08T23:59:16Z Eight-lesson series covering the full custom training workflow on TT hardware: dataset fundamentals, configuration patterns, fine-tuning, multi-device distributed training, experiment tracking, model architecture basics, and training from scratch.

Links: Understanding Custom Training · Dataset Fundamentals · Configuration Patterns · Fine-tuning Basics · Multi-Device Training · Experiment Tracking · Model Architecture Basics · Training from Scratch

By tsingletaryTT · affiliated · added 2026-05-08

training, fine-tuning, multi-device, distributed, experiment-tracking, curriculum, guides, ai-models

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/ct8-training-from-scratch/ Custom Model Training on Tenstorrent — Training from Scratch 2026-05-08T23:59:15Z Eight-lesson series covering the full custom training workflow on TT hardware: dataset fundamentals, configuration patterns, fine-tuning, multi-device distributed training, experiment tracking, model architecture basics, and training from scratch.

Links: Understanding Custom Training · Dataset Fundamentals · Configuration Patterns · Fine-tuning Basics · Multi-Device Training · Experiment Tracking · Model Architecture Basics · Training from Scratch

By tsingletaryTT · affiliated · added 2026-05-08

training, fine-tuning, multi-device, distributed, experiment-tracking, curriculum, guides, ai-models

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/cookbook-overview/ Tenstorrent Cookbook: Core Recipes — Tenstorrent Cookbook Overview 2026-05-08T23:59:14Z Three hands-on TT-Metalium kernel recipes: a Mandelbrot fractal explorer, real-time audio signal processing pipeline, and custom image filter stack. Each recipe is a complete kernel project with full source in the lesson.

Links: Tenstorrent Cookbook Overview · Recipe 3: Mandelbrot Fractal Explorer · Recipe 2: Audio Signal Processing · Recipe 4: Custom Image Filters

By tsingletaryTT · affiliated · added 2026-05-08

cookbook, mandelbrot, audio, image-processing, metalium, demo, kernels, guides

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/cookbook-mandelbrot/ Tenstorrent Cookbook: Core Recipes — Recipe 3: Mandelbrot Fractal Explorer 2026-05-08T23:59:13Z Three hands-on TT-Metalium kernel recipes: a Mandelbrot fractal explorer, real-time audio signal processing pipeline, and custom image filter stack. Each recipe is a complete kernel project with full source in the lesson.

Links: Tenstorrent Cookbook Overview · Recipe 3: Mandelbrot Fractal Explorer · Recipe 2: Audio Signal Processing · Recipe 4: Custom Image Filters

By tsingletaryTT · affiliated · added 2026-05-08

cookbook, mandelbrot, audio, image-processing, metalium, demo, kernels, guides

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/cookbook-audio-processor/ Tenstorrent Cookbook: Core Recipes — Recipe 2: Audio Signal Processing 2026-05-08T23:59:12Z Three hands-on TT-Metalium kernel recipes: a Mandelbrot fractal explorer, real-time audio signal processing pipeline, and custom image filter stack. Each recipe is a complete kernel project with full source in the lesson.

Links: Tenstorrent Cookbook Overview · Recipe 3: Mandelbrot Fractal Explorer · Recipe 2: Audio Signal Processing · Recipe 4: Custom Image Filters

By tsingletaryTT · affiliated · added 2026-05-08

cookbook, mandelbrot, audio, image-processing, metalium, demo, kernels, guides

]]> https://docs.tenstorrent.com/tt-vscode-toolkit/lessons/cookbook-image-filters/ Tenstorrent Cookbook: Core Recipes — Recipe 4: Custom Image Filters 2026-05-08T23:59:11Z Three hands-on TT-Metalium kernel recipes: a Mandelbrot fractal explorer, real-time audio signal processing pipeline, and custom image filter stack. Each recipe is a complete kernel project with full source in the lesson.

Links: Tenstorrent Cookbook Overview · Recipe 3: Mandelbrot Fractal Explorer · Recipe 2: Audio Signal Processing · Recipe 4: Custom Image Filters

By tsingletaryTT · affiliated · added 2026-05-08

cookbook, mandelbrot, audio, image-processing, metalium, demo, kernels, guides

]]> https://clehaxze.tw/gemlog/2024/07-07-a-gentle-guide-on-getting-your-tenstorrent-card-running-on-arch-linux-with-the-metalium-stack.gmi A Gentle Guide: Tenstorrent Card on Arch Linux with Metalium — clehaxze.tw — July 2024 2026-05-08T23:59:10Z Step-by-step guide to getting a Tenstorrent card running on Arch Linux with the full Metalium stack. Practical troubleshooting from someone who did it the hard way first.

Links: clehaxze.tw — July 2024

By Martin Chang · community · added 2026-05-08

arch-linux, metalium, installation, blog, getting-started, guides, blogs

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