Solutions

Parallelization & Optimization Your Way

Solutions for every workflow and pipeline.

TALPification
as a Service
Beta by Invite
GitHub
GitLab
Bitbucket
Highly-Available · Maintenance Free · On-Demand
Have code that needs to be TALP parallelized and optimized today? Get started immediately by connecting your repositories and getting on-demand optimization. All you need is 5-minutes to sign-up, get connected and witness the awesome speedup of TALPs.
Self-Hosted
TALPification
Coming Soon
Git
Mercurial
Subversion
Sovereign & Secure · Privately Parallelize
Keep your code and workflows managed entirely in-house. Massively Parallel's TALP engine will be deployed on your servers, behind your firewalls. Your code never leaves your environment.
Enterprise Services
By Request
Execute on saving time and energy today.
Work directly with Massively Parallel engineers. Together we will identify the areas of your organization's applications and algorithms that benefit most from TALP parallelization and optimization.
Automatic On-Deploy
TALPification
On Roadmap
AWS
Azure
GCP
JIT Architecture-Targeted Parallelization & Optimization
Make optimization part of your deployment process. Integrate Massively Parallel's TALP engine with your deployment tool pipeline. Code will be TALP parallelized and optimized for the target architecture's execution environment based on pre-configured cost, energy and speedup goals.
IDE-Based
TALPification
On Roadmap
VS Code
Eclipse
Vim
Uninterrupted: Parallelize Where You Code
Don't ever leave your code. Our in-IDE solutions allow for you to make TALPs a part of your daily workflow. No new tools to learn. No new integrations into your dev toolchain. Just a simple extension and your same algorithms are better, faster and more efficient.
TALP MCP Server
On Roadmap
OpenAI
Claude
Cursor
Coding AgentsMPT's TALPs MCP Server
Connect AI applications and agents directly to MPT's Model Context Protocol (MCP), enabling agents to access all our TALP Engine's analysis and optimization tools, expediting AI's ability to make TALPs a part of AI workflows and code generation.

TALPification as a Service

Connect a repo, analyze time pathways (TALPs), optimize for speed or energy, and return TALPified code + reports.

OBJECTIVESpeedEnergyBalanced
INPUT

GitHub Repository

Private or public • read-only pull • customer-controlled source of truth

Example tree
$ git clone …
/src
/include
/tests
C/C++/Rust/…
Code never locked in
TALPIFICATION ENGINE

Secure Cloud TALPification Engine

Whole-program analysis → finds Time-Affecting Linear Pathways → rewrites execution in time

A
Ingestion & Parsing
Pull code, parse, and build a whole-program representation.
B
TALP Analysis Core
Find time pathways & overlap potential. Not just task splitting—time restructuring.
C
Optimization Objective Selector
Tune for speed, energy, or a balanced tradeoff.
D
Architecture Targeting
Optimize for target architectures and deployment configurations.
Target profiles
x86ARMRISC-VCloud/HPC
OUTPUTS

TALPified Source Code

Same logic • time-restructured execution

Performance & Energy Report
Expected speedup, power/cooling impact, and guidance.
Deployment Metadata
Target arch + config, CI/CD-ready outputs.
Same code • new time flow
Key idea

Same code. Same logic. Different execution in time. TALPification reshapes when code executes — not just where.

TALPification as a Service (Cloud / SaaS)Connect repo analyze time pathways (TALPs) optimize for speed/energy return TALPified code + reportsINPUTTALPIFICATION ENGINEOUTPUTSGitHub Repository Private or public repo Read-only access (service pulls code) Customer-controlled source of truth$ git clone/src/include/testsC/C++/Rust/CODE NEVER LOCKED INSecure Cloud TALPification EngineWhole-program analysis identifies Time-Affecting Linear Pathways rewrites execution in timeA) Ingestion & ParsingPull code, parse, build whole-program representationB) TALP Analysis CoreFind time pathways & overlap potentialNot just task splitting time restructuringC) Optimization Objective SelectorSpeedEnergyBalancedD) Architecture Targetingx86 / ARM / RISC-V single-node / cluster cloud configsProduces optimized code tailored to deployment environmentx86ARMRISC-VCloud/HPCOutputsTALPified Source Code Same logic Time-restructured executionPerformance & Energy Report Expected speedup Power/cooling impactDeployment Metadata Target arch + config CI/CD-ready outputsSAME CODE NEW TIME FLOWSame code. Same logic. Different execution in time.TALPification reshapes when code executes not just where.IDE TALPification PluginTALPify code from within your editor — analyze, optimize, and apply changes without leaving the IDEDEVELOPERIDE PLUGINOUTPUTSIDE Workspace• Local project or repo checkout• Works on a branch / PR workflow• Developer controls changesmain.cfor (i=0; i<n; i++) step(a[i]);&rbrace;RUN TALPIFICATION IN IDEMPT IDE ExtensionAnalyze your code, choose objectives, preview changes, and apply TALPified updatesA) Local Analysis & ContextUnderstands project structure and dependenciesB) TALP Analysis CoreFind time pathways & overlap potentialRestructure execution timing (not task splitting)C) Objective SelectorSpeedEnergyBalancedD) Preview + ApplyDiff view, annotations, and one-click applyCommit TALPified changes to a branch or PROutputsTALPified Code Changes• IDE diff + annotations• Applied to branch / PRPerformance & Energy Report• Expected speedup• Power/cooling impactTarget Profiles• Laptop / workstation / server• x86 / ARM / cloud configsSTAYS IN YOUR DEV WORKFLOWSame engine. Same TALPs. Integrated into the editor for faster iteration.Preview changes, apply safely, and commit with confidence.Self-Hosted TALPification EngineFull TALPification capability deployed inside customer infrastructure — no code leaves the environmentCUSTOMER INFRASTRUCTURESELF-HOSTED TALPIFICATION ENGINEOUTPUTSOn-Prem / Private Cloud• Corporate data center• Private cloud (VPC)• Air-gapped / regulated networksInternal Git ServerGitHub Enterprise / GitLab / BitbucketCI / CD PipelineBuild • Test • DeploySecure Compute ClusterHPC • Servers • Private CloudCODE NEVER LEAVES YOUR NETWORKMPT TALPification Engine (Self-Hosted)Identical TALP logic as cloud service, deployed locally1) Local Ingestion & ParsingPulls from internal repos only2) TALP Analysis CoreDiscovers Time-Affecting Linear PathwaysRewrites execution order in time3) Policy & Objective ControlsSpeed • Energy • Deterministic execution4) Architecture TargetingOptimized for local hardware & schedulersLocal OutputsTALPified Source CodeStored in internal reposPerformance / Energy ReportsInternal visibility onlyCI / Runtime IntegrationUsed by schedulers & build systemsFULL IP & DATA SOVEREIGNTYAll computation, analysis, and outputs remain inside customer-controlled infrastructureOn-Demand Runtime TALPificationExecution-aware optimization: TALPify code at submit-time based on available hardware, cost, and energy constraintsJOB SUBMISSIONRUNTIME TALPIFICATION SERVICEEXECUTIONCode + Run IntentSubmitted to cloud / data center / HPC queuesubmit_job( src="repo@commit", goal="balanced", max_cost="$",)PER-RUN OPTIMIZATION REQUESTConstraints (Examples)• Deadline / SLA• Cost ceiling• Energy or carbon budget• Preferred architecturesRuntime TALPification ServiceTALPifies for the specific execution environment and current operational conditions1) Environment DiscoveryQuery available resources: CPU types, nodes, acceleratorsRead current pricing / power / scheduling constraints2) Objective + Constraint SolverSelects best tradeoff per runFastestLowest EnergyLowest Cost3) TALP Analysis + Rewrite (Per Run)Find time pathways, reshape execution timing for target environmentGenerates run-specific TALPified artifacts4) Package + DispatchDeliver optimized code/binary to the selected runtime poolNear-real-time TALPification at submit-timeSelected Execution PoolRuns TALPified artifacts on best-fit resourcesPool A: Fastest NodesHigh performance • higher costPool B: Energy-OptimizedLower power • lower thermal loadPool C: Lowest CostSpot / off-peak • budget-firstOPTIMIZED FOR THIS RUNOptional: telemetry improves future run decisionsKey idea: TALPification can be execution-aware — optimized per run, per environment, per cost/energy goal.

Services: Work with MPT to Optimize and Parallelize Your Code

Energy
Speed

Energy Analysis

Optimized Energy Use
379.08 Ws
Serial Energy Use
3,258.57 Ws
Energy Savings
2,879.48 Ws
88.37%
.