Oct 24, 2026

From WordPiece to Ranked BPE: What a Tokenizer Really Does

A visual math log of WordPiece, BPE, SentencePiece, special tokens, and exact token-ID contracts in CKE.

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Oct 13, 2026

From Generated C to Useful Agents: CKE Serving Qwen Code and Gemma4

CKE now serves bounded Qwen Code and Gemma4 agent tasks from generated native CPU bundles. Here is what passed, what failed, and why batching remains a separate gate.

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Oct 3, 2026

What Changed in C-Kernel-Engine This September

September was the month C-Kernel-Engine started to feel less like a collection of model demonstrations and more like a system I could keep extending. That is not the same as saying it is fin...

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Sep 27, 2026

I Want To Use My Linux Workstation Without Looking At It

I Want To Use My Linux Workstation Without Looking At It I have spent a lot of time building software that lets me run AI models on CPUs. Now I want to use some of that work for a more perso...

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Sep 23, 2026

From Native Kernels to Generated Audio Circuits: Parakeet and Cohere in CKE

A measured two-CPU investigation of how CKE moved Parakeet and Cohere into generated C, including six complete 42-minute runs, exact cross-host transcripts, performance bottlenecks, and rema...

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Sep 19, 2026

How Ericsson Edge Routers Shaped CKE

My Ericsson work combined Linux systems programming with a larger router architecture spanning service discovery, IPC, recursive lookup, TCAM, NPUs, DPDK and live forwarding. Those two layer...

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Sep 13, 2026

How to Get Started With C-Kernel-Engine on Linux

Run CKE manually or use the included local coding-agent prompt to inspect Linux, install dependencies, execute a small Gemma model, and preserve the evidence.

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Sep 9, 2026

What CKE Fixed Today: Honest Evidence and Faster CPU Whisper

CKE hardened its evidence and Whisper runtime, culminating in persistent workers that cut a controlled 42:22 transcription from 171.60 to 138.73 seconds without changing retained outputs.

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Sep 6, 2026

How CKE Brought Up Qwen3.8 Flash Next

Qwen3.8 Flash Next brought hyper-connections, Per-Layer Embedding, recurrent DeltaNet, query-selected sparse attention and mixed packed experts into one CKE circuit. This is what changed, wh...

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Sep 5, 2026

Qwen3.8 Broke In CKE. Our Regression Tests Needed To Catch It.

I have been writing about how quickly C-Kernel-Engine is adding model families. Qwen3.8 had already produced useful output in CKE, so I treated that support as progress we had earned. Then i...

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Sep 5, 2026

I Used CKE To Transcribe My Video. It Found A Bug In My Compiler.

Yesterday I recorded the second video in my kernel engineering series. Since C-Kernel-Engine already had Whisper support, I wanted to use it to transcribe my own recording. Not another small...

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Sep 2, 2026

How Audio Becomes Words: Whisper's Kernels, Step By Step, On A CPU

A kernel-by-kernel walkthrough of how C-Kernel-Engine runs Whisper end to end in generated FP32 C: the eight signal-processing frontend kernels that turn a WAV into 1500 tokens, the full sti...

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Aug 26, 2026

CKE Now Runs More Than Qwen: Cohere, Laguna, Instella, Nemotron And More

A detailed look at CKE's expanded model-family matrix, what each architecture added to the kernel portfolio, and why support must be reported with an evidence level rather than one generic c...

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Aug 25, 2026

One Ryzen, 128K Context, And A 27B Model: What Qwen3.8 Generated With CKE

Two measured Qwen3.8-27B runs used a real 128K prompt on one Ryzen CPU to generate complete technical SVGs, then exposed CKE's next cache, traffic and distributed-computing targets.

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Aug 23, 2026

CKE Added Qwen3.8 In About An Hour. The Architecture Is Starting To Pay Off

Qwen3.8 became an explicit CKE model circuit without a runtime fork or a new arithmetic kernel. Merged Ryzen bring-up and 4,000-step X-Ray certification show what reusable numerical provider...

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Aug 22, 2026

CKE Zip: From Splitting Tokens To Splitting Qwen3.5 Weights

How CKE moved from token-row prefill sharding to a weight-sharded Qwen3.5 transformer block, what reconstructed correctly, and why one Ryzen still beats the current heterogeneous pair.

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Aug 22, 2026

I Spent CAD $9,575 Building CKE's CPU AI Lab

A receipt-backed account of CKE's founder-funded Intel and AMD CPU lab, the experiments each node unlocks, and the controlled access path planned for collaborators.

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Aug 21, 2026

Training vs Inference in CKE: One Interface Discipline For Both Lanes

CKE is not inference-only. Six DSL hardening PRs taught the compiler to reject quiet boundary mismatches: map interfaces, port-vs-ABI validation, ranked providers, and faithful traces — on...

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Aug 20, 2026

The Qwen3-VL CPU Gap vs llama.cpp: A Build Log That Keeps Getting Measured

CKE moved a Qwen3-VL OCR path from ~281s to ~76.7s against a llama.cpp baseline of ~55.8s — not a victory lap, a map. Revisited after the harness era: corpus certification, X-Ray parity, a...

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Aug 5, 2026

Training vs Inference in CKE: One Interface Discipline For Both Lanes

CKE is not inference-only. The v7 training and v8 inference lanes share one compiler-interface discipline.

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Aug 4, 2026

A Green Checkmark Should Name Its Machine: How CKE's Nightly Report Became Evidence

A green CI badge is an argument, not a decoration. CKE's nightly report now captures and publishes its runner's hardware identity, renders it as an amber identity plate, and teaches operator...

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Aug 3, 2026

LinuxUtilities: My Personal Linux Control Layer For AI, Publishing, And C-Kernel-Engine Work

How LinuxUtilities connects AwesomeWM, a native GTK4 control center, screenshots, audio, storage, presentation tools, AI prompts, and CKE work — including the path-contract bug that made t...

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Aug 2, 2026

How CKE Made Whisper Faster In Two Days — And The Evidence That Makes It Believable

The two days after the July books closed The July recap closed its Whisper chapter at a 2.7x gap to whisper.cpp: 1.53–1.58 seconds on the controlled Base fixture against 0.567 seconds for ...

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Aug 1, 2026

What CKE Built In July 2026: Vision, Audio, X-Ray And Faster CPU Inference

A source-linked July recap of 194 PRs and 32 articles: multimodal models, long-context numerical parity, compiler and test hardening, CPU evidence, contributors, and the path toward distribu...

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Jul 31, 2026

How CKE Made Qwen3.6 Prefill 2.6x Faster

How CKE used exact head parallelism and packed quantized kernels to accelerate Qwen3.6-27B Q4_K_M prefill 2.6x on one 5th Gen Xeon node, while remaining about 1.85x behind llama.cpp.

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Jul 29, 2026

How CKE X-Ray Found Qwen3.6's First Bad Circuit

Follow a real CKE X-Ray investigation from a wrong Qwen3.6 token to a grouped recurrent-topology mismatch, including what passes and what remains open.

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Jul 28, 2026

Kimi K3 Open Weights: What Is Actually New In Its 2.8-Trillion-Parameter Architecture?

Read Kimi K3 from its released config, model code, and technical report: the new kernels, the role of scale and training, and what a distributed CPU runtime would need to implement.

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Jul 27, 2026

Memory Planning in C-Kernel-Engine

Memory Planning in C-Kernel-Engine In CKE, memory planning is not a nice cleanup pass after the kernels are written. It is part of the model contract: which buffer holds the current stream, ...

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Jul 26, 2026

Teaching C-Kernel-Engine To Listen: Whisper Tiny, End To End On v8

An earlier article explained how an audio transformer hears: waveform to frames, frames to log-Mel features, features to encoder states, states to decoded text. This article is the implement...

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Jul 24, 2026

Hugging Face Got Hacked By A Closed Model. A Closed Model Also Refused To Help Fix It.

A closed OpenAI evaluation model compromised Hugging Face, while hosted models later refused forensic evidence. The incident strengthens the case for open weights and practical local CPU AI.

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Jul 23, 2026

What Numerical Parity Actually Requires: BF16, Quantization, ISA Drift And CKE X-Ray

Numerical parity is not one BF16 tolerance. Trace how CKE uses llama.cpp, PyTorch, X-Ray, replay provenance and phase-owned kernel contracts to locate the first divergence.

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Jul 22, 2026

Softmax vs Softplus: Competition, Positive Gates, and Backpropagation

Derive softmax and softplus, trace Laguna's learned gate projection through full attention and backpropagation, and compare where modern model families use softplus.

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Jul 21, 2026

GLM4 Bring-Up In CKE: What A New Model Family Actually Requires

A source-backed walkthrough of how C-Kernel-Engine brings up GLM4 through model contracts, tensor mapping, pairwise partial RoPE, generated C, parity tools, and explicit evidence boundaries.

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Jul 20, 2026

Qwen3.5 Hybrid Recurrent Attention: How DeltaNet State And Full Attention Share One Decoder

Trace Qwen3.5's hybrid circuit, see how CKE X-ray finds numerical divergence, and separate exact runtime parity from the observed quality of a 0.8B model.

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Jul 19, 2026

Prefill vs Decode in CKE: Why One Model Needs GEMM, GEMV, and Two Execution Plans

Follow an LLM request from tokenization through prefill, KV-cache construction and decode, then see why CPU projections become GEMM or GEMV and how CKE compares them with llama.cpp.

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Jul 18, 2026

CKE Kernel Registry: How Exact C Functions And Numerical Contracts Connect

How CKE resolves model circuits to exact C kernel providers, preserves numerical contracts through IR, and generates correct stitched code.

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Jul 16, 2026

What Is A CPU PMU? How perf, VTune And Advisor Measure What A Processor Actually Did

How PMU hardware, Linux perf_event_open, Intel Xeon and AMD EPYC counters, sampling, uncore monitoring, and profiler tools turn processor activity into reproducible optimization evidence.

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Jul 15, 2026

What kernel.kptr_restrict=0 Actually Does: Linux Profiling, Kernel Symbols, VTune And Advisor

Why Linux profiler permissions, kernel symbol visibility, PMU compatibility, and application debug symbols are separate evidence boundaries.

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Jul 14, 2026

Nemotron Kernels From Inference To Backpropagation

A visual, source-linked derivation of Nemotron inference, training forward, backpropagation, and quantization across Mamba2, attention, ReLU2, and routed experts.

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Jul 13, 2026

Nemotron Is Not One Circuit: Mamba, Attention, And MoE Routing

How Nemotron mixes recurrent state, attention, dense MLP, and routed experts, and why exact routing becomes a CPU memory and scheduling problem.

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Jul 12, 2026

Gemma4-VL In CKE: How Images Become Decoder Tokens

How Gemma4-VL turns image patches into decoder-width visual tokens, why its vision bridge differs from Qwen3-VL, and how CKE is preparing compatibility.

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Jul 11, 2026

Gemma4 In CKE: Four Attention Paths, Shared KV, And Sliding Windows

How C-Kernel-Engine represents Gemma4 attention and per-layer RoPE from model metadata through IR, kernel maps, and generated C.

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Jul 10, 2026

Templates Are Circuit Maps: How CKE Describes A Model Family

How C-Kernel-Engine model-family templates declare architecture, dataflow, lowering, memory, generated C, and evidence gates on Linux CPUs.

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Jul 9, 2026

GGUF: The File Format That Made Local LLMs Practical

GGUF: The File Format That Made Local LLMs Practical Format deep dive GGUF is not just a container for weights. It is a single-file deployment unit that carries the model architecture, token...

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Jul 8, 2026

Amdahl's Law, Theory Of Constraints, And C-Kernel-Engine Optimization

A systems-performance note connecting Amdahl's Law, Theory of Constraints, transformer inference, multi-node CPU scaling, and how C-Kernel-Engine optimizes runtime paths by measuring the act...

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Jul 7, 2026

DeepSeek-V4 Architecture From Kernels: mHC, CSA, HCA, DSA, and C-Kernel-Engine

A kernel-level reading of DeepSeek-V4: mHC residual lanes, CSA/HCA compressed attention, DSA sparse selection, MoE dispatch, low precision, and what those ideas mean for C-Kernel-Engine.

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Jul 6, 2026

How the Jacobian Matrix Works

.jacobian-matrix-post .math-block { display: block; max-width: 100%; overflow-x: auto; overflow-y: hidden; -webkit-overflow-scrolling: touch; margin: 1rem 0; padding: 0.85rem 1rem; border: 1...

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Jul 5, 2026

How Audio Transformers Work: The Encoder Path, Whisper, Timestamps, And Why Audio Is Not A VLM Patch

How Audio Transformers Work: The Encoder Path, Whisper, Timestamps, And Why Audio Is Not A VLM Patch Audio transformers use the same high-level trick as language and vision transformers: con...

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Jul 4, 2026

DeltaNet vs SSM: Two Fixed-Size Memory Systems Beyond Attention

C-Kernel-Engine architecture note DeltaNet and SSM/Mamba are two ways to reduce the amount of unbounded attention history a model has to carry by introducing fixed-size learned state. They a...

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Jul 3, 2026

Nemotron Architecture From A C-Kernel-Engine Runtime Perspective

C-Kernel-Engine architecture note Nemotron-style hybrid models are interesting to C-Kernel-Engine because they stop looking like a simple stack of attention plus MLP blocks. A runtime has to...

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Jul 2, 2026

K-Quants Deep Dive: Q4_K, Q5_K, Q6_K, Q8_K And Mixed Dot Products

ML systems · Quantization internals This ShivasNotes deep dive is the granular companion to the broader Quantization Deep Dive in this series. The earlier post explained why quantization ma...

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Jul 1, 2026

Threadpools And Memory Pools: Why CKE Needs Runtime Ownership For CPU AI Kernels

C-Kernel-Engine runtime comparison This post is a follow-up to the earlier thread-pool deep dive. The previous post built the pthread idea from first principles. This one asks the systems qu...

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Jun 30, 2026

Pipeline vs Tensor Parallelism: How CKE Splits AI Across CPU Nodes

Distributed runtime note C-Kernel-Engine has been hardened first as a CPU-native runtime on single machines. The next phase is not just buying faster CPUs. It is learning how to make multipl...

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Jun 29, 2026

Distributed CPU AI: MPI, RDMA, NUMA, and C-Kernel-Engine

Systems note This post moves from model math into the machine that actually runs the kernels: cores, caches, NUMA domains, MPI ranks, RDMA-capable fabrics, and the memory-layout discipline n...

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Jun 28, 2026

Muon Optimizer: SGD vs AdamW vs Matrix-Aware Training Updates

Muon vs AdamW explained from update mathematics to optimizer state, PyTorch's BF16 Newton-Schulz implementation, matrix-aware training kernels, memory cost, and a proposed C-Kernel-Engine pa...

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Jun 27, 2026

Kernel Engineers Are Worth Billions In 2026: Chris Lattner, Mojo, LLVM, and the Compiler Layer of AI

Kernel Engineers Are Worth Billions In 2026: Chris Lattner, Mojo, LLVM, and the Compiler Layer of AI Compiler systems note Chris Lattner's career is a reminder that compiler engineers and ke...

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Jun 26, 2026

Linux System Programming For AI Kernels: Core Pinning, Huge Pages, TLBs, NUMA, and Memory Discipline

Systems note A fast kernel is not just a loop. A fast kernel is a loop, a memory layout, a thread placement policy, a page-fault policy, and a measurement discipline running inside a real Li...

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Jun 25, 2026

KV Cache Memory: The Hidden State That Makes LLM Decode Work

KV cache memory for CPU-native inference This ShivasNotes deep dive is written for engineers who want to understand the single largest memory consumer in autoregressive LLM inference: the KV...

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Jun 24, 2026

v8 IR Pipeline Codegen: How CKE Hardens Pure-C Inference

v8 inference hardening This ShivasNotes deep dive is written for engineers who want to understand what happens between "here is a model on Hugging Face" and "here is a compiled .so that runs...

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Jun 22, 2026

CPU Performance Engineering for AI: Rooflines, Flamegraphs, VTune, and Perf Gates

CPU performance engineering · C-Kernel-Engine This ShivasNotes deep dive is written for CPU silicon teams and systems engineers who need to understand not just whether an AI framework is fa...

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Jun 21, 2026

Flash Attention on CPU: Online Softmax, Cache Discipline, and C-Kernel-Engine

ML fundamentals This ShivasNotes deep dive is written for CPU silicon teams asking a very specific question: does C-Kernel-Engine really own attention on CPU down at the kernel layer? The an...

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Jun 20, 2026

Quantization Deep Dive: How CPU Kernels Compress Weights and Preserve Accuracy

Quantization deep dive · ML fundamentals This ShivasNotes deep dive is written for CPU silicon teams evaluating whether C-Kernel-Engine really owns its quantized inference path. The answer ...

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Jun 19, 2026

ARM NEON in C-Kernel-Engine: Real Quantized Kernels on ARM

ARM NEON · C-Kernel-Engine CKE has already run Qwen2 and Qwen3 on ARM Cortex-A72 hardware (TI TDA4VM). This is not a roadmap post. This is a “what we already ship” post. For ARM silicon...

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Jun 18, 2026

SIMD Deep Dive: How AI Kernels Use SSE, AVX, AVX-512, and VNNI

ML fundamentals · SIMD deep dive This ShivasNotes deep dive is written for CPU silicon teams evaluating kernel-level software competence. The subject is not “can the model run?” but “...

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Jun 17, 2026

How Qwen3-VL Vision Works: Header Body Footer

Lab note This ShivasNotes lab note studies how a real vision-language model turns images into tokens that a language decoder can use. It connects earlier notes on activations, normalization,...

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Jun 16, 2026

Gated DeltaNet: Recurrent Attention With Error-Driven Memory

Lab note This ShivasNotes lab note studies the alternative used by the Qwen3.5 / qwen3next recurrent path in C-Kernel-Engine: Gated DeltaNet, where the model stops trying to store every toke...

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Jun 15, 2026

Optimizers: From SGD to AdamW

Lab note Part of the ShivasNotes transformer-from-scratch series. Previously: dL/d(LLM): The Full Backward Pass. The full backward-pass post ended with every weight in the model holding a gr...

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Jun 14, 2026

AI Kernel Engineer Beginner Guide: Math, Linear Algebra, C/Linux

AI Kernel Engineer Beginner Guide: Math, Linear Algebra, C/Linux Part 1: Beginner roadmap A viewer asked a useful question: “I know some C, some linear algebra, and some calculus. What are...

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Jun 13, 2026

Thread Pools in C: How CPU Runtimes Dispatch Work Across Cores

Thread Pools in C: How CPU Runtimes Dispatch Work Across Cores Runtime note Companion note for the threadpool video. This post zooms into the local runtime layer: how persistent workers rece...

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Jun 12, 2026

dL/d(LLM): The Full Backward Pass

A capstone walkthrough of the full LLM backward pass: loss to LM head, final norm, decoder layers, attention, FFN, residual splits, embedding scatter-add, training loop, AdamW, and C-Kernel-...

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Jun 11, 2026

Residual Connections: The Gradient Highway

Lab note Previously: Attention: The Core Of The Transformer. The previous post showed how attention routes information sideways across a sequence. This post is about the architectural trick ...

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Jun 10, 2026

Attention: The Core Of The Transformer

Attention is the core transformer mechanism: Q/K/V projections, head splitting, RoPE, scaled dot-products, masking, softmax, weighted value sums, GQA, Flash Attention, and the full backward ...

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Jun 9, 2026

Tokenization: The First Decision That Shapes Everything

Lab note Companion post to the Tokenization carousel. Previously: Positional Encoding: Teaching Transformers Where To Look. Tokenization is the first place where text stops being human langu...

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Jun 8, 2026

Positional Encoding: Teaching Transformers Where To Look

Lab note Companion post to the Positional Encoding carousel. Previously: LayerNorm And RMSNorm: Stabilizing The Signal. Transformers are brilliant at reading an entire sequence in parallel, ...

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Jun 7, 2026

LayerNorm And RMSNorm: Stabilizing The Signal

Lab note Companion post to the LayerNorm & RMSNorm carousel. Watch the companion video: Why LayerNorm and RMSNorm Matter in a C LLM Runtime. Previously: Activation Functions: The Nonlinearit...

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Jun 6, 2026

Activation Functions: The Nonlinearity Inside Neural Networks

Lab note Companion post to the Activation Functions carousel. Previously: Softmax: The Probability Engine. The previous Softmax post ended with a strange contrast. Softmax was beautifully sm...

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Jun 5, 2026

Softmax: The Probability Engine

Lab note Companion post to the Softmax carousel. Previously: Matrix Wx+b: From Scalars To Transformers. The previous post was about the moment a scalar weighted sum grew into a matrix multip...

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Jun 4, 2026

Matrix Wx+b: From Scalars To Transformers

A step-by-step explanation of how scalar wx+b becomes matrix Wx+b, how shape rules govern transformer layers, and why GEMM is the physical kernel underneath modern models.

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Jun 3, 2026

Backpropagation From wx+b: The Smallest Training Loop

Lab note This is the companion post to today's backprop-wxplusb carousel. I wanted a version with more room for the pictures, the algebra, and the engineering intuition. Previous post in thi...

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May 31, 2026

Why I Build Things From Scratch

Why I keep building systems from scratch: Antsand, C Kernel Engine, and my flight-controller stack all come from the same instinct to understand primitives, remove bloat, think like a compil...

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May 31, 2026

Training SVGs With C Kernel Engine: A Research Report

A research-style report on training small C Kernel Engine models to emit SVG-oriented DSLs, showing why lower loss is not enough, how tokenizer and compiler contracts shaped the work, and wh...

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May 29, 2026

Hardening My Linux Engineering Workflow

I am slowly moving more of my engineering life back into Linux. Not as a slogan. As a workflow. This is part two of my hardening series. Part one was Hardening Long Projects in the Age of A...

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May 26, 2026

What Is the C Kernel Engine?

Abstract / Executive Summary C Kernel Engine is an AI LLM inference and training engine optimized for CPUs. It takes model weights, model configuration, and computational graph templates, th...

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May 24, 2026

Is the Future of My Work Writing, Typing, Drawing, and Orchestrating?

For the last few months, I have been noticing a strange shift in my work. I am still building software. I am still thinking about AI runtimes, Linux, C Kernel Engine, Antsand, content system...

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May 20, 2026

Qwen3 From a C Runtime Perspective

Qwen3 is not just a model name inside C Kernel Engine. It is a concrete runtime target: a GGUF file, a model configuration, a set of tensor shapes, a generated C runtime, a packed weight blo...

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May 15, 2026

Hardening Long Projects in the Age of AI

Images generated by chatGPTI have been thinking a lot about hardening lately, especially with Antsand. Not hardening in the dramatic cybersecurity movie sense. I mean the boring kind of hard...

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Apr 21, 2026

Why I Stopped Getting High on the Newer AI Models (And Why My Strategic Bet Is Still Consistent: CPUs, Smaller Models, and Less Compute Will Win)

Last week, Claude Opus 4.7 "got released." And the Anthropic team is doing what Americans are genius at: marketing, marketing, marketing. The whole Claude, OpenAI, Gemini saga is the same pl...

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