Powered by TRAAVIIS

TickTickClock

Bulk Synchronous Parallel for Elixir

Declarative, type-safe distributed computing with predictable performance. Build parallel algorithms that scale from laptops to supercomputersโ€”deadlock-free, always.

Get Started View on GitHub
defmodule MyApp.PageRank do
  use TickTickClock.BSP

  # Declarative superstep definition
  superstep :calculate_rank do
    # Compute phase - runs in parallel
    compute fn vertex ->
      new_rank = 0.15 + 0.85 * sum(vertex.inbox)
      {:ok, %{vertex | rank: new_rank}}
    end

    # Communication phase - automatic synchronization
    communicate do
      send_to :neighbors, fn vertex ->
        contribution = vertex.rank / length(vertex.edges)
        Enum.map(vertex.edges, &{&1, contribution})
      end
    end

    # Convergence check
    converged? fn old, new ->
      abs(new.rank - old.rank) < 0.0001
    end
  end
end

Why TickTickClock?

The power of BSP, the elegance of Elixir, the reliability of BEAM

๐ŸŽฏ

Declarative First

Define what to compute, not how to synchronize. Focus on your algorithm, not barriers and locks.

๐Ÿ”’

Type-Safe

Stellarmorphism integration ensures compile-time guarantees. Catch errors before runtime.

๐Ÿ“Š

Predictable Performance

BSP cost model (w + hยทg + l) lets you predict execution time before running.

๐Ÿšซ

Deadlock-Free

Bulk synchronous barriers eliminate race conditions and deadlocks by design.

โšก

BEAM-Native

Leverage OTP supervision, distribution, and fault tolerance. Run on any BEAM cluster.

๐Ÿ“ก

Real-Time Observable

Phoenix LiveView dashboards show superstep progress, processor status, and metrics.

๐Ÿ”„

Composable

Mix BSP computations with OPEN workflows, Ash resources, and regular Elixir code.

๐Ÿ“

Scales Up & Down

From single-core development to thousand-node clusters. Same code, different scale.

๐Ÿงช

Testable

Deterministic execution makes parallel algorithms easy to test and debug.

Built For Real Problems

From social networks to supercomputers

๐ŸŒ

Graph Analytics

PageRank, shortest paths, community detection

๐Ÿงฌ

Scientific Computing

Molecular dynamics, N-body simulations

๐Ÿค–

Machine Learning

Distributed gradient descent, model training

๐Ÿ“Š

Data Analytics

MapReduce, sorting, aggregation at scale

๐Ÿš—

Fleet Optimization

Route planning, traffic flow, coordination

๐Ÿ’ฐ

Financial Systems

Risk calculation, portfolio optimization

๐Ÿ–ผ๏ธ

Image Processing

Segmentation, filtering, computer vision

๐ŸŽฎ

Real-Time Systems

Game synchronization, multiplayer state

How It Works

The BSP model: Compute โ†’ Communicate โ†’ Synchronize

1. Local Computation Processors work in parallel on local data โ†“
2. Communication Exchange messages between processors โ†“
3. Barrier Synchronization All processors wait until everyone completes โ†“
Next Superstep Repeat until convergence or termination ๐Ÿ”

Part of a Stellar Ecosystem

TickTickClock integrates seamlessly with your Elixir stack

๐ŸŒŸ Stellarmorphism

  • Type-safe data structures
  • Compile-time validation
  • Pattern matching with fission
  • Asteroid & rocket recursion

๐Ÿ”„ OPEN Sentience

  • DAG workflow orchestration
  • Mix BSP with traditional tasks
  • Distributed execution
  • OTP supervision trees

๐Ÿ—บ๏ธ WebHost.systems

  • GPS tracking infrastructure
  • TimescaleDB integration
  • PostGIS spatial queries
  • Real-time fleet coordination

๐Ÿ”ฅ Ash Framework

  • Declarative resource patterns
  • Action-based API
  • Multi-tenant isolation
  • Authorization policies

๐ŸŽญ Phoenix LiveView

  • Real-time dashboards
  • Superstep visualization
  • Performance metrics
  • Zero JavaScript needed

โš™๏ธ BEAM Ecosystem

  • OTP fault tolerance
  • Distributed Erlang
  • GenServer processors
  • Telemetry integration

Ready to Build?

Join the future of parallel computing in Elixir. TickTickClock brings supercomputer algorithms to BEAM.

Get Started Read the Docs
^ADVERTISEMENT