Processor IP

PROMETHEUS

Dataflow AI Processor IP

Revolutionary dataflow architecture optimized for AI workloads with spatial compute arrays, intelligent memory hierarchies, and runtime reconfigurable elements

Dataflow-Optimized Architecture: Prometheus leverages spatial computing with reconfigurable dataflow graphs, eliminating traditional bottlenecks through intelligent data movement and compute orchestration across configurable processing elements.

Performance Leadership

Superior performance-per-watt ratio that sets industry benchmarks

Highly Configurable

Dataflow architecture with configurable spatial compute arrays, memory hierarchies, and AI-optimized interconnects

Integration Ready

Optimized for rapid SoC integration with minimal effort

Future-Proof

Architecture designed for emerging workloads and technologies

Target Customer Segments

Prometheus IP is strategically positioned for diverse market segments, each with unique requirements and value propositions

Tier-1 SoC Vendors

Primary Target

Key Companies

Qualcomm
MediaTek
Broadcom

Primary Need

Differentiated processor cores for flagship chipsets

Value Proposition

Performance leadership, power efficiency, time-to-market

Positioning Strategy

Key Message

"The performance core that defines next-generation flagship chipsets"

Focus Areas
Benchmark leadership
Architectural innovations
Ecosystem support

Competitive Differentiation

Prometheus stands apart from key competitors through strategic advantages in performance, ecosystem, and integration

vs ARM Cortex

Superior performance/watt, more flexible licensing

vs RISC-V

Optimized microarchitecture, enhanced AI acceleration, comprehensive configuration tools

vs x86

Lower power, better integration, cost advantage

vs Custom Designs

Faster time-to-market, proven reliability

Extensive Configuration Options

Prometheus dataflow architecture offers extensive configurability across spatial compute arrays, memory hierarchies, and dataflow orchestration - optimized for diverse AI workloads from edge inference to large-scale training

Spatial Compute Arrays

  • • Dataflow Processing Units (4-64)
  • • Memory Reconfigurable Units (4-64)
  • • AI Acceleration Elements (8-128)
  • • Spatial grid dimensions (4x4 to 16x16)
  • • Configurable tensor data paths (128-1024 bits)

Memory Hierarchy

  • • 3-tier memory system
  • • Register file (1K entries)
  • • VMEM (16MB, 16-bank parallel)
  • • HBM external memory
  • • Configurable bank sizes (64KB-1MB)

Precision & Data Types

  • • FP32, FP16, BF16, FP8 support
  • • INT8, INT4 quantization
  • • Custom precision formats
  • • Dynamic precision switching
  • • Mixed-precision workloads

Dataflow Interconnects

  • • Spatial dataflow routing
  • • Configurable tensor buses (64-512 bits)
  • • Multi-dimensional data movement
  • • AI workload-optimized QoS
  • • High-bandwidth inter-chip links

Power & Clock Domains

  • • Independent clock domains (2-8)
  • • Dynamic voltage scaling
  • • Power mode selection (4 modes)
  • • Clock gating and power islands
  • • Thermal management

Virtualization & Security

  • • Hardware virtualization (up to 8 instances)
  • • 256-bit encryption per instance
  • • Memory protection units
  • • Secure boot and HSM support
  • • Side-channel attack protection

Advanced Configuration & Runtime Reconfiguration

Prometheus features comprehensive configuration tools and unique runtime reconfiguration capabilities that adapt to changing workload characteristics in real-time.

Compile-Time Configuration

50+ RTL parameters, CGRA mapping options, grid dimensions, precision modes, and device templates

Framework Integration

Native PyTorch, ONNX, TensorFlow backends with automatic precision and resource optimization

Runtime Reconfiguration

Dynamic workload adaptation, performance monitoring, and element type reconfiguration

Pre-configured Templates

Edge: 4x4 grid, optimized for power •Standard: 8x8 grid, balanced performance •Datacenter: 16x16 grid, maximum throughput

Technical Excellence

Prometheus delivers industry-leading specifications across all key metrics

Performance

40%

Better performance/watt than leading alternatives

Efficiency

60%

Lower power consumption in AI workloads

Integration

3x

Faster SoC integration time

Ready to Transform Your Next SoC?

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