CROSS-PLATFORM SOFTWARE RUNTIME

AltiCoreSWP: Massive Throughput at Matched Accuracy

28x* *

Speed Versus Neural Networks

Enterprise data centers are hitting the "Arithmetic Wall." Conventional neural networks rely on dense matrix math, forcing a costly dependency on specialized GPUs and power-heavy accelerators to scale performance.

AltiCoreSWP replaces heavy arithmetic with logic-dominant operator chains. In benchmark evaluations at equivalent accuracy, it delivered 13x to 28x throughput gains on standard CPU speedups, maximizing performance on your existing infrastructure without hardware modifications.

Realized with SidePath

Operational benchmarks

“AltiCore performance is transformative. Seeing a software synthesis engine outperform established best-in-class Neural Networks solution by such a massive margin signals a fundamental shift in AI deployment. AltiCore seems to be at the beginning of its journey. I am sure there will be a lot of room for optimizations leading to even higher performance.”
— Patrick Mulvee, CEO, SidePath

Laptop

Mobile Workstation Dell Precision 5680 | Intel i7-13700H | 32GB RAM | No GPU

i7-Gen13CPU-execution Only

Enterprise / Datacenter Server

Dell PowerEdge R760 | Intel Xeon Gold 5416S

Xeon GoldMax Rack Density

AltiCoreSWP Vs. Neural Networks (Laptop)

Dataset
Multicore Python
C++ TensorFlow XNN
C++ TensorFlow RUY MT
Credit Default
41x
7x
27x
Credit Fraud
51x
7x
20x
Give Me Some Credit
42x
14x
43x
Mfg (High Eff)
50x
13x
64x
Mfg (Low Eff)
50x
13x
73x
Machine Failure
32x
10x
24x
Spect
82x
21x
92x

AltiCoreSWP Vs. Neural Networks (Server) **

Dataset
Multicore Python
C++ TensorFlow XNN
C++ TensorFlow RUY MT
Credit Default
98x
40x
40x
Credit Fraud
88x
17x
18x
Give Me Some Credit
63x
15x
54x
Mfg (High Eff)
103x
19x
90x
Mfg (Low Eff)
107x
19x
97x
Machine Failure
85x
9x
32x
Spect
143x
28x
110x

Global Accuracy

AltiCore
Neural Network

AltiCore vs Neural Network

Inference Gains

Median: 9.9x
Geo-Mean: 9.3x

AltiCore on Laptop vs Best Neural Network on Server

AltiCoreSWP on laptop beats neural networks on server

AltiCoreSWP restructures legacy workloads into logic-dominant operator chains, achieving such massive efficiency that a mobile workstation easily outpaces a server-class execution.

Benchmark Example: Credit Fraud Detection

AltiCoreSWP Laptop (Inf/Sec)

361,010,000

Server Neural Network (Inf/Sec)

30,090,000

Speed Multiplier

12x

What is AltiCoreSWP

  • Order-of-Magnitude Throughput: Delivers massive gains in decisions per second on standard general-purpose compute.
  • Arithmetic Wall Solution: Replaces heavy matrix arithmetic with mathematically efficient, logic-dominant operator chains.
  • Zero-Change Deployment: Optimized for existing CPU infrastructure, requiring no hardware accelerators or NPU upgrades.
  • Logic-Based Synthesis: Trains models from scratch directly into logic-centric primitives for maximum execution efficiency.
  • Superior Unit Economics: Maximizes inferences per watt, directly reducing the total cost of ownership for AI scaling.

Key Features

  • Reduced Arithmetic Intensity: Dramatically minimizes floating-point overhead by leveraging hardware-native logical operations.
  • Massive Throughput: Achieved peak speedups up to 27.6x faster than highly optimized C++ neural network baselines.
  • AVX2 Optimization: Specifically tuned for high-speed, vectorized execution on standard enterprise architectures
  • Steady-State Efficiency: Optimized for sustained, massive-scale throughput rather than isolated micro-latency.
  • Horizontal Scalability: Integrates cleanly into standard dev-ops workflows for rapid, hardware-agnostic deployment across clusters.

Why AltiCoreSWP is Different

  • Bypasses GPU Dependency: Enables high-speed AI on CPUs, removing the bottleneck of specialized, costly hardware accelerators.
  • Logic-Dominant Execution: Replaces traditional floating-point tensor overhead with mathematically efficient, discrete logic.
  • Infrastructure Revitalization: Extends the lifecycle of existing server racks by enabling massive AI throughput on current hardware.
  • Reduced Thermal Load: Lower computational complexity significantly reduces energy draw and data center cooling requirements.
  • On-Premises Security: CPU-only execution allows high-speed AI to remain entirely within your secure enterprise boundary.
MASSIVE CAPEX & OPEX SAVINGS

Strategic Advantage

Maximize Existing CPU ROI

Achieve observed peak throughput speedups up to 28x on existing workstation and server CPUs. Extend the utility of current hardware assets by eliminating the requirement for expensive, supply-constrained GPU upgrades.

Optimized Logic Synthesis

Bypass the “Arithmetic Wall” by replacing resource-heavy matrix math with mathematically efficient, logic-dominant operator chains. This fundamental shift in computation radically reduces thermal overhead and energy consumption per inference.

Seamless Stack Integration

Deploy high-throughput workloads on Windows and Linux using automated conversion into highly portable C/C++ templates. Ensure rapid deployment and horizontal scaling with minimal changes to existing DevOps pipelines or software architectures.

OS & HARDWARE SUPPORT

Technical Compatibility

Target Infrastructure

  • Windows and Linux OS
  • Native laptop, desktop, server support
  • Optimized for x86 via AVX2

Implementation Paths

  • Supports standard C/C++ and Python workflows
  • Optional CUDA support for GPU scaling
  • Unified inference and training framework

Operational Integrity

  • Logic-dominant; drastically reduces FPU usage
  • Deterministic, repeatable execution behavior
  • CPU-first performance without GPU reliance
Corporate Inquiries

Connect with EvoChip Management

For media or partnership opportunities, contact us directly.

Email

contact@evochip.ai

Headquarters

32932 Pacific Coast Hwy

Dana Point, CA