🚀 Turkish Sieve Engine (TSE) V.1.0.0

Unique, Compact & Massive-Parallel Prime Discovery Engine

📌 Introduction

Turkish Sieve Engine (TSE) is a revolutionary application that combines unprecedented computational efficiency, compact memory structures, and massive parallelization in prime number research.

Based on the scientific methodology published on Zenodo (DOI: 10.5281/zenodo.18038661)

TSE is the most efficient academic tool designed for the detection of primes, twin primes, and cousin primes within any given range, including massive scales ($10^{14}$ and beyond) .

📊 Key Metrics & Achievements

• Peak Throughput: 181.5 Billion candidates/sec (measured on RTX 3070 @ $10^{12}$ range).
• Memory Efficiency: N/6 bit data structure (6x more compact than classical sieves).
• GPU Acceleration: Up to 11.0× speedup compared to multi-core CPUs in optimal ranges.
• Scientific Accuracy: 100% compliance with OEIS A007508 (Zero error margin for twin&cousin primes).
• First Achievement: Successful full enumeration of cousin primes up to the $10^{14}$ limit.

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💎 Why is TSE Unique?

1. No Modular Arithmetic

Unlike traditional sieving algorithms, TSE replaces expensive MOD/DIV operations with simple integer additions (n <- n+p).

This hardware-friendly approach eliminates the heavy computational overhead of division in GPU/HPC architectures.

2. Extreme Memory Efficiency

The canonical $N/3$ bit sieve structure has been reduced to an $N/6$ bit representation by leveraging the mathematical nature of $(p, p+2)$ and $(p, p+4)$ pairs. This allows processing 100 trillion numbers ( for $10^{14}$) using only 1.1 GB of VRAM.

3. Seamless Compactness & UI/UX

• No Coding Knowledge Required: A fully menu-driven, interactive interface for researchers.
• Smart Hardware Detection: Automatically analyzes system CPU and GPU specifications (Cores, Cache, VRAM).
• Professional Reporting: Generates detailed performance metrics after every analysis.

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📝 Sample Performance Analysis Report

TSE generates detailed reports showing the architectural efficiency of the system:

*************************** NEW REPORT ***********************
==============================================================
                PERFORMANCE ANALYSIS & REPORT
                     2026-01-17 15:11:49
==============================================================
 Engine Type        : GPU Segmented Sieve (Cuda Parallel.)
 Device             : NVIDIA GeForce RTX 3070
 Range Start        : 1
 Range End          : 1,000,000,000,000
 Type               : TWIN PRIME
 Total Process Time : 5 s 510 ms
 TOTAL PAIRS FOUND  : 1,870,585,220
 --------------------------------------------------------------
 Throughput         : 181.488 G-items/s
 CUDA Occupancy     : %83.3 (Architectural Efficiency)
 Speed (Decimal)    : 181488.203 Million/s
 Speed (Binary)     : 173080.638 Mi/s
 System RAM Usage   : 281 MB
 GPU VRAM Usage     : 1127 MB
 --------------------------------------------------------------
 >> 181,488,203,266 numbers checked per second
===============================================================
This report is the result of the TSE V.1.0.0 application.
************************** END OF REPORT **********************

*************************** NEW REPORT ***********************
==============================================================
                PERFORMANCE ANALYSIS & REPORT
                     2026-01-17 15:54:30
==============================================================
 Engine Type        : GPU Segmented Sieve (Cuda Parallel.)
 Device             : NVIDIA GeForce RTX 3070
 Range Start        : 1
 Range End          : 100,000,000,000,000
 Type               : TWIN PRIME
 Total Process Time : 2264 s 706 ms
 TOTAL PAIRS FOUND  : 135,780,321,665
 --------------------------------------------------------------
 Throughput         : 44.156 G-items/s
 CUDA Occupancy     : %83.3 (Architectural Efficiency)
 Speed (Decimal)    : 44155.842 Million/s
 Speed (Binary)     : 42110.292 Mi/s
 System RAM Usage   : 314 MB
 GPU VRAM Usage     : 1145 MB
 --------------------------------------------------------------
 >> 44,155,841,862 numbers checked per second
===============================================================
This report is the result of the TSE V.1.0.0 application.
************************** END OF REPORT **********************

*************************** NEW REPORT ***********************
==============================================================
                PERFORMANCE ANALYSIS & REPORT
                     2026-01-17 19:49:20
==============================================================
 Engine Type        : GPU Segmented Sieve (Cuda Parallel.)
 Device             : NVIDIA GeForce GTX 1650 Ti
 Range Start        : 1,000,000,000,000,000
 Range End          : 1,001,000,000,000,000
 Type               : TWIN PRIME
 Total Process Time : 348 s 447 ms
 TOTAL PAIRS FOUND  : 1,106,775,692
 --------------------------------------------------------------
 Throughput         : 2.870 G-items/s
 CUDA Occupancy     : %100.0 (Architectural Efficiency)
 Speed (Decimal)    : 2869.877 Million/s
 Speed (Binary)     : 2736.928 Mi/s
 System RAM Usage   : 279 MB
 GPU VRAM Usage     : 886 MB
 --------------------------------------------------------------
 >> 2,869,876,910 numbers checked per second
===============================================================
This report is the result of the TSE V.1.0.0 application.
************************** END OF REPORT **********************

*************************** NEW REPORT ***********************
==============================================================
                PERFORMANCE ANALYSIS & REPORT
                     2026-01-17 05:05:49
==============================================================
 Engine Type        : CPU Multi-Core Segmented (OMP Parallel.)
 Device             : Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz
 Range Start        : 0
 Range End          : 100,000,000,000
 Type               : COUSIN PRIME
 Total Process Time : 12 s 177 ms
 TOTAL PAIRS FOUND  : 224,373,161
 --------------------------------------------------------------
 Throughput         : 8.212 G-items/s
 Compute Strategy   : High-Throughput Mode
 Speed (Decimal)    : 8212.203 Million/s
 Speed (Binary)     : 7831.767 Mi/s
 System RAM Usage   : 150 MB
 GPU VRAM Usage     : 0 MB
 --------------------------------------------------------------
 >> 8,212,203,334 numbers checked per second
===============================================================
This report is the result of the TSE V.1.0.0 application.
************************** END OF REPORT **********************

🚀 How to Use (Step-by-Step)

System Requirements

• GPU: NVIDIA CUDA Compute Capability 3.5+ (RTX/GTX Series).

• CPU: Intel/AMD x86-64 (with OpenMP support).

• OS: Currently Windows 10/11 only.

Download Ready-to-Run Package

Get the pre-built Windows executable (ZIP package) from the latest release:

Or visit the Releases page directly.

Run Tse_v100.exe.

The application will automatically detect your hardware (Cores, Cache, GPU, VRAM).

Security & VirusTotal Scan

TSE_v100.exe scanned on VirusTotal (70+ engines):
Clean & Safe – 0 detections (no threats found)

View full report
SHA256: 041b8984563be0133e9cfed872df9740ca6bf2749ad59366f85216b6bd705afb
(Scanned: January 19, 2026)

Select from the Main Menu:

• [1] GPU MODE: Uses the CUDA engine for maximum performance.

• [2] CPU MODE: Uses the multi-core statistical engine.

• Enter Parameters: Start (N), End (M), and Prime Type (1: Twin, 2: Cousin).

• Once the analysis is complete, press the Y key to save the results as analysis_log.rtf

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📊 Global Benchmarking & Community Contributions

We are building a comprehensive, community-driven performance database to showcase how the Turkish Sieve Engine (TSE) performs across different hardware architectures (consumer GPUs, high-end workstations, multi-core CPUs, etc.).

Your contributions help scientifically validate the N/6 bit methodology, mirror symmetry optimizations, and overall efficiency gains — especially at scales beyond 1e09.

How to Contribute Your Benchmarks

1. Run any test range in TSE.
2. When prompted, select "Save Results (Y)".
3. The application will automatically generate two key files:
   • analysis_log.rtf — detailed performance metrics (throughput, runtime, candidates/sec, etc.)
   • engine_config.txt — your hardware & system specs (CPU, GPU VRAM, CUDA version, OS, etc.)
4. Email both files to: bilgisoft.tr@gmail.com
   Include your preferred name/nickname (or "anonymous" if you wish to stay private) in the email body.

We will:

• Verify the results for consistency and validity
• Add your entry to the public Global Benchmark Leaderboards in the User Benchmarks folder
• Rank entries by average time (fastest at the top) within each range
• Give shoutouts to top performers on X (@turkishsieve) and in the repository

Example leaderboard files:

• 0 – 1e14 Twins Leaderboards
• 0 – 1e14 Cousins Leaderboards
• and more ranges as data arrives…

Other Ways to Support the Project

• Star the Repository ⭐
  If you're a researcher, student, developer or enthusiast using TSE, please give the repo a star. It significantly increases visibility in the scientific and open-source communities and motivates continued development of the N/6 bit approach.

• Share Your Experience
  Post your results, questions or suggestions on GitHub Discussions, Issues, or X (@turkishsieve). Community feedback directly shapes future releases.

Thank you in advance to everyone who contributes — your runs are helping push the boundaries of deterministic prime-pair sieving on consumer hardware!

Questions? Just open an issue or reply on X. Let's build this together! 🚀

📂 Repository Structure

• user-benchmarks/ → Last users scor tables.

• bin/ → Executable files.

• docs/ → All importand files, figures, and documentation.

🔮 Roadmap

v1.1.0 (2026 H2): Multi-GPU support (NVLink), GMP Integration (after the $2^{64}$ limit).

v2.0.0+: Distributed computing (MPI), AI-optimized sieving patterns, and FPGA support.

⚖️ Licensing & CitationAcademic Use:

Free of charge with full capacity but time-limited (1 hour) access for researchers and the scientific community.

Commercial Use:

Subject to a licensing agreement for enterprise integration and commercial use.

Details:

See the LICENSE.md file for more information.

⚖️ Citation

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If you use the Turkish Sieve Engine or the N/6 Bit Methodology in your research, please cite the original work using the following format:

APA Style

ÇAKANLI, H. (2025). The Turkish Sieve Methodology: Deterministic Computation of Twin and Cousin Prime Pairs Using an N/6 Bit Data Structure (V.1.0.0). Zenodo. https://doi.org/10.5281/zenodo.18038661

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💡 Other Styles (BibTeX, RIS, MLA, etc.)

You can export this citation in various formats directly from the official Zenodo page: 👉 View and Export Citations on Zenodo

DOI: 10.5281/zenodo.18038661

Contact & Licensing: 📧 bilgisoft.tr@gmail.com

🔬 Academic Metadata & Publication Details

The methodology behind this engine is formally documented as a scientific preprint. Below are the official publication details:

• Document Title: The Turkish Sieve Methodology: Deterministic Computation of Twin and Cousin Prime Pairs Using an N/6 Bit Data Structure
• Persistent Identifier (DOI): 10.5281/zenodo.18038661
• Resource Type: Preprint (Scientific Paper)
• Publisher: Zenodo
• Primary Language: English
• Release Date: 2025

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🤝 Support and Sponsorship

This project aims for unprecedented computational efficiency.

We welcome any hardware sponsorship (for high-capacity server testing and multi-vendor GPU development), donations, or technical suggestions.

To partner in the development of this engine, please open an Issue on GitHub or contact us directly.