Nodepp is a vertically integrated C++ runtime engineered to solve the Efficiency Paradox of modern distributed computing. While managed runtimes prioritize developer velocity at the cost of hardware overhead, Nodepp delivers industry-leading throughput with a near-zero resource footprint through deterministic memory management and hardware-aligned architecture.
By unifying the event reactor, protocol parsers, and memory controller into a single architectural DNA, Nodepp eliminates the Abstraction Tax that inflates infrastructure costs and energy consumption.
Scaling the Talent Bridge for Green Computing: Achieving Silicon-Logic Parity through Deterministic RAII — A Roadmap for Distributed Systems in the Post-Moore Era and Heterogeneous System Fragmentation. Read the full technical breakdown, including architectural deep-dives into ptr_t, kernel_t and coroutine_t.
Nodepp is designed for Resource Density. While modern runtimes often throw hardware at the problem, Nodepp optimizes the software to respect the silicon. By reducing memory overhead and CPU jitter, we directly decrease the energy footprint of digital infrastructure.
Test: 100k requests | 1k Concurrency | Environment: Localhost | Device: Educational-grade Dual-Core Apollo lake Chromebook see benchmark
| Metric | Bun (v1.3.5) | Go (v1.18.1) | Nodepp (V1.4.0) | Impact |
|---|---|---|---|---|
| Requests / Sec | 5,985 | 6,139 | 6,851.33 | +11.6% Performance |
| Memory (RSS) | 69.5 MB | 14.1 MB | 2.9 MB | 95.8% Reduction |
| Max Latency | 1,452 ms | 326 ms | 245 ms | Elimination of GC Spikes |
| p99 Latency | 1,159 ms | 249 ms | 187 ms | High-precision SLA stability |
| Energy Efficiency | Low | Medium | Extreme | Maximum hardware utilization |
Test: 1k Cycles | 100k Allocations | Environment: Educational-grade Dual-Core Apollo lake Chromebook see benchmark
| Runtime | Avg. Cycle Time | VIRT (Address Space) | RES (Physical RAM) | Memory Model |
|---|---|---|---|---|
| Nodepp | 3.0 ms (±0.1 ms) | 6.1 MB | 2.7 MB | Deterministic RAII |
| Bun | 7.2 ms (5-11 ms range) | 69.3 GB | 72.6 MB | Generational GC |
| Go | < 1.0 ms* | 703.1 MB | 2.2 MB | Concurrent GC |
Note: Go's <1ms measurement reflects allocation latency only; reclamation is deferred to concurrent garbage collection cycles.
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Infrastructure Density: Nodepp's 2.9 MB footprint enables 23× more services per physical host compared to Bun, reducing hardware requirements and data center cooling loads.
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Deterministic Energy Draw: By eliminating garbage collection spikes, Nodepp maintains stable CPU utilization, extending IoT battery life and lowering cloud power consumption.
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E-Waste Reduction: Nodepp's ability to run advanced asynchronous logic on 8-bit/32-bit microcontrollers prevents hardware forced obsolescence, extending the usable lifetime of existing hardware.
Rooted in Electrical Engineering principles, Nodepp implements hardware-centric design patterns to mitigate the systemic flaws of high-level runtimes:
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Deterministic Latency: Eliminates the unpredictable spikes of Garbage Collection (GC) through manual, reference-counted memory safety.
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Zero Heap Fragmentation: Employs a fragmentation-resistant memory model
ptr_toptimized for long-running asynchronous processes. -
Scale-Invariant Logic: Enables the same high-level logic to run with parity across the hardware spectrum — from 8-bit microcontrollers to 64-bit clustered cloud servers.
Nodepp implements its own protocol parsers ( HTTP, WebSocket ) specifically to ensure they are Poll-Aware. By building these engines directly on the kernel_t reactor core:
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Mechanical Sympathy: Data moves from the system-socket directly into logic. This removes the Copy Tax found in generic libraries.
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Cache Locality: Sharing the memory logic with the core reactor keeps data hot in the L1/L2 cache, significantly reducing latency jitter.
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Reactor Backends: Supports native event-multiplexing via Epoll (Linux), IOCP (Windows), Kqueue (BSD/Mac) and busy-while loop ( embedded systems ).
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Concurrency Model: Shared-nothing architecture with isolated workers to prevent lock contention.
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Cross-Platform Parity: Designed to maintain logic consistency across 8-bit/32-bit Microcontrollers (Arduino), WebAssembly (WASM), and POSIX-compliant operating systems.
This example demonstrates the integration of the event loop with a basic HTTP reactor, showcasing the unified API style.
#include <nodepp/nodepp.h>
#include <nodepp/regex.h>
#include <nodepp/http.h>
#include <nodepp/date.h>
#include <nodepp/os.h>
using namespace nodepp;
void onMain() {
auto server = http::server([]( http_t cli ){
cli.write_header( 200, header_t({
{ "content-type", "text/html" }
}) );
cli.write( regex::format( R"(
<h1> hello world </h1>
<h2> ${0} </h2>
)", date::fulltime() ));
cli.close();
});
server.listen( "0.0.0.0", 8000, []( socket_t /*unused*/ ){
console::log("Server listening on port 8000");
});
}The Nodepp project is supported by a suite of modular extensions designed to follow the same unified design patterns:
- Data Parsing: XML
- Tor: Torify, JWT.
- Security: Argon2,
- Web: ExpressPP, ApifyPP.
- IoT/Embedded: SerialPort, Bluetooth.
- Databases: Redis, Postgres, MariaDB, Sqlite.
Nodepp is the only framework that lets you share logic between the deepest embedded layers and the highest web layers.
- Hardware: NodePP for Arduino
- Desktop: Nodepp for Desktop
- Browser: Nodepp for WASM
- IOT: Nodepp for ESP32
Nodepp is an open-source project that values Mechanical Sympathy and Technical Excellence.
- Sponsorship: Support the project via Ko-fi.
- Bug Reports: Open an issue via GitHub.
- License: MIT.
Nodepp is distributed under the MIT License. See the LICENSE file for more details.
