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Simulation and scientific computing
physics-daq
particle physics trigger and data acquisition
CERN LHC
System
Techniques · 9
Primitives · 40
physics-daq
Clock synchronization
distributed · medium: Estimate a clock's offset from four timestamps, filter out queueing noise, and steer the clock smoothly; NTP gets about a millisecond, PTP with hardware timestamps under a microsecond.
›
Fpga dataflow pipelines
hardware-os · medium: Fully pipelined fixed-latency FPGA logic: initiation interval, HLS, BRAM and DSP budgeting
Gradient-boosted decision trees (GB…
machine-learning · medium: Add small regression trees one at a time, each fitted to the loss gradient; histogram splits over 256 bins make it the strongest tabular default.
›
Hough transform
robotics · medium: Vote in parameter space to detect lines, circles and particle tracks
Columnar storage
storage · medium: Store each column contiguously so analytic scans read only the columns they need, compress well and run as tight SIMD loops.
›
Instruction scheduling
compilers · medium: List scheduling over dependence DAGs with latency models; software pipelining of loops
Static timing analysis
hardware-os · medium: Propagate latest/earliest arrival forward and required times backward through a DAG; slack = required - arrival, and the minimum-slack path is the critical one.
›
LZ4
compression · low: Byte-aligned LZ77 with no entropy stage; compresses at hundreds of MB/s and decompresses at several GB/s per core, for when speed beats ratio.
›
SPSC ring buffer
data-structures · low: Bounded wait-free queue for exactly one producer and one consumer thread, built from an array and two indices with acquire/release ordering.
›
Deterministic fixed-point math
game-networking · low: Bit-identical simulation math across CPUs, compilers and builds: integer fixed-point formats, the float traps (FMA, x87, fast-math, libm), deterministic trig, sqrt and RNG.
›
Buffer pools for zero-allocation I/O
hardware-os · low: Preallocate a fixed set of aligned I/O buffers and recycle them through a free list, so the hot path never mallocs, faults or unmaps. The bounded count doubles as back pressure.
›
CRC32C checksums
hardware-os · low: The Castagnoli CRC-32 with dedicated instructions on x86 (SSE4.2) and ARMv8. It is the standard fast integrity check for storage blocks, logs and network frames.
›
Weight quantization
ml-training · low: Store weights as 8/4-bit integers with per-group scales; decode is memory-bound, so 4-bit weights give about 3-4x tokens/s and fit 4x larger models.
›
Kernel-bypass networking
networking · low: User space (DPDK, AF_XDP) or an in-driver eBPF hook (XDP) handles packets straight from NIC rings, skipping sockets, for 10-40 Mpps per core.
›
Rdma
networking · low: RDMA verbs over InfiniBand/RoCE: queue pairs, memory registration, one-sided ops
Kalman filter
robotics · low: Optimal recursive estimator for a linear system with Gaussian noise: fuses a motion model with noisy measurements into a state estimate plus its covariance.
›
Zero suppression
signal-processing · low: Drop samples under threshold at readout and encode sparse hits with addresses
PID controller
robotics · low: Drive a measured value to a setpoint with three terms on the error: proportional, integral, derivative. The default feedback loop for motors, heaters, drones and gimbals.
›
Phase-locked loop (digital)
signal-processing · low: Feedback loop that locks a local oscillator to the phase and frequency of an input tone; the core of carrier recovery, clock recovery and GNSS tracking.
›
Robust statistics
statistics · low: Location and scale estimates (median, MAD, trimmed mean, Huber M-estimator) that stay correct when a minority of the data is garbage.
›
Quantile sketches
data-structures · low: Mergeable quantile sketches: t-digest, DDSketch, HDR histograms
Loss functions
machine-learning · low: The scalar a model minimizes: cross-entropy for classes and tokens, MSE or Huber for values, each with a stable form and simple gradient.
›
Regularization
machine-learning · low: Techniques that trade training fit for generalization: weight decay, dropout, early stopping, label smoothing and data mixing, with the exact update rules and defaults.
›
+ 2 more techniques
+ 24 more primitives
System
Techniques · 9
Primitives · 40
physics-daq
Clock synchronization
distributed · medium: Estimate a clock's offset from four timestamps, filter out queueing noise, and steer the clock smoothly; NTP gets about a millisecond, PTP with hardware timestamps under a microsecond.
›
Fpga dataflow pipelines
hardware-os · medium: Fully pipelined fixed-latency FPGA logic: initiation interval, HLS, BRAM and DSP budgeting
Gradient-boosted decision trees (GB…
machine-learning · medium: Add small regression trees one at a time, each fitted to the loss gradient; histogram splits over 256 bins make it the strongest tabular default.
›
Hough transform
robotics · medium: Vote in parameter space to detect lines, circles and particle tracks
Columnar storage
storage · medium: Store each column contiguously so analytic scans read only the columns they need, compress well and run as tight SIMD loops.
›
Instruction scheduling
compilers · medium: List scheduling over dependence DAGs with latency models; software pipelining of loops
Static timing analysis
hardware-os · medium: Propagate latest/earliest arrival forward and required times backward through a DAG; slack = required - arrival, and the minimum-slack path is the critical one.
›
Vectorized execution
storage · medium: Query operators pass batches of about 1-2K values per column instead of single tuples, amortizing interpretation overhead and enabling tight SIMD loops.
›
Critical path analysis
graphs · medium: Longest dependency chain in a DAG of timed spans or build actions
LZ4
compression · low: Byte-aligned LZ77 with no entropy stage; compresses at hundreds of MB/s and decompresses at several GB/s per core, for when speed beats ratio.
›
SPSC ring buffer
data-structures · low: Bounded wait-free queue for exactly one producer and one consumer thread, built from an array and two indices with acquire/release ordering.
›
Deterministic fixed-point math
game-networking · low: Bit-identical simulation math across CPUs, compilers and builds: integer fixed-point formats, the float traps (FMA, x87, fast-math, libm), deterministic trig, sqrt and RNG.
›
Buffer pools for zero-allocation I/O
hardware-os · low: Preallocate a fixed set of aligned I/O buffers and recycle them through a free list, so the hot path never mallocs, faults or unmaps. The bounded count doubles as back pressure.
›
CRC32C checksums
hardware-os · low: The Castagnoli CRC-32 with dedicated instructions on x86 (SSE4.2) and ARMv8. It is the standard fast integrity check for storage blocks, logs and network frames.
›
Weight quantization
ml-training · low: Store weights as 8/4-bit integers with per-group scales; decode is memory-bound, so 4-bit weights give about 3-4x tokens/s and fit 4x larger models.
›
Kernel-bypass networking
networking · low: User space (DPDK, AF_XDP) or an in-driver eBPF hook (XDP) handles packets straight from NIC rings, skipping sockets, for 10-40 Mpps per core.
›
Rdma
networking · low: RDMA verbs over InfiniBand/RoCE: queue pairs, memory registration, one-sided ops
Kalman filter
robotics · low: Optimal recursive estimator for a linear system with Gaussian noise: fuses a motion model with noisy measurements into a state estimate plus its covariance.
›
Zero suppression
signal-processing · low: Drop samples under threshold at readout and encode sparse hits with addresses
PID controller
robotics · low: Drive a measured value to a setpoint with three terms on the error: proportional, integral, derivative. The default feedback loop for motors, heaters, drones and gimbals.
›
Phase-locked loop (digital)
signal-processing · low: Feedback loop that locks a local oscillator to the phase and frequency of an input tone; the core of carrier recovery, clock recovery and GNSS tracking.
›
Robust statistics
statistics · low: Location and scale estimates (median, MAD, trimmed mean, Huber M-estimator) that stay correct when a minority of the data is garbage.
›
Quantile sketches
data-structures · low: Mergeable quantile sketches: t-digest, DDSketch, HDR histograms
Loss functions
machine-learning · low: The scalar a model minimizes: cross-entropy for classes and tokens, MSE or Huber for values, each with a stable form and simple gradient.
›
Regularization
machine-learning · low: Techniques that trade training fit for generalization: weight decay, dropout, early stopping, label smoothing and data mixing, with the exact update rules and defaults.
›
Convolution image filters
graphics · low: Separable 2D convolution kernels for blur, sharpen (unsharp mask) and edges with border handling
Peak detection
signal-processing · low: Robust peak and event detection in noisy signals with adaptive thresholds and refractory periods
Bit packing and PFOR
compression · low: Store blocks of integers with exactly b bits each and patch rare outliers separately (PFOR); the fastest integer codec family, billions of values per second.
›
Delta encoding
compression · low: Store differences between consecutive values instead of the values, turning sorted IDs, timestamps and counters into small numbers that pack into few bits.
›
Dictionary encoding
compression · low: Map values to small integer codes via a dictionary for compact, comparable columns
Zone maps
storage · low: Per-block min/max (and sparse primary) indexes to skip data during scans
d-ary heap
data-structures · low: Array heap with d children per node (d = 4 typical): half the binary heap's depth, siblings in one cache line, faster priority queues.
›
Topological sort
graphs · low: Order the vertices of a DAG so every edge points forward; the core of build systems, schedulers and dependency resolution, with cycle detection for free.
›
Instruction pipelining
hardware-os · low: Pipeline stages, hazards, forwarding and stalls in CPU cores
BFS and DFS
graphs · low: The two basic graph traversals; BFS gives hop distances and levels, DFS gives discovery/finish order for cycles, components and topological order.
›
Varint (LEB128)
compression · low: Variable-length integers in 7-bit groups with a continuation bit; small numbers take 1 byte, the wire format of Protobuf, WebAssembly and DWARF.
›
False sharing
concurrency · low: Independent variables written by different cores on one cache line force the line to bounce between cores; pad or regroup hot data to fix it.
›
Memory ordering
concurrency · low: What Relaxed, Acquire, Release and SeqCst atomics actually guarantee, what they cost on x86 and ARM, and which one each pattern needs.
›
CPU caches and the memory hierarchy
hardware-os · low: Sizes, line widths and latencies of L1/L2/L3/DRAM on modern x86 and Apple M-series, and the data-layout rules that follow from them.
›
fsync, O_DSYNC and O_DIRECT
hardware-os · low: What fsync, fdatasync, O_DSYNC, O_DIRECT and F_FULLFSYNC really guarantee on Linux and macOS, and the exact call sequences for crash-safe files.
›
Huge pages
hardware-os · low: 2 MB/1 GB pages to cut TLB misses; THP vs explicit hugetlbfs
Numa aware allocation
hardware-os · low: Allocate memory and pin threads on the local NUMA node; first-touch and interleave policies
SIMD programming
hardware-os · low: Process 4-16 lanes per instruction with AVX2, AVX-512 or NEON via Rust std::arch, with runtime dispatch and a portable fallback.
›
Ebpf xdp
networking · low: EBPF programs at the XDP/tc hooks for in-kernel packet processing at line rate
Receive side scaling
networking · low: NIC hashing of flows to RX queues (RSS) and symmetric hashing for per-core processing
Low precision number formats
numerics · low: Bf16, fp16, fp8 (E4M3, E5M2), MX block formats and int4: ranges, rounding, scaling
LU and Cholesky factorization
numerics · low: Factor A = PLU (any square matrix, partial pivoting) or A = LLᵀ (SPD) once in O(n³), then solve each right-hand side in O(n²).
›
PRNGs (PCG, xoshiro)
numerics · low: Small, fast, statistically strong non-cryptographic generators: PCG32 and xoshiro256**, with seeding, parallel streams and unbiased ranges.
›
Sparse matrices (CSR)
numerics · low: Compressed sparse row stores only nonzeros as row pointers, column indices and values; SpMV streams them once, so it is memory-bandwidth bound.
›
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