GSI Technology, Inc.
Climate Impact & Sustainability Data (2023)
Reporting Period: 2023
Environmental Metrics
Total Carbon Emissions:Not disclosed
Scope 1 Emissions:Not disclosed
Scope 2 Emissions:Not disclosed
Scope 3 Emissions:Not disclosed
Renewable Energy Share:Not disclosed
Total Energy Consumption:Not disclosed
Water Consumption:Not disclosed
Waste Generated:Not disclosed
Carbon Intensity:Not disclosed
ESG Focus Areas
- Climate Change
- Energy Efficiency
Environmental Achievements
- Not disclosed
Social Achievements
- Not disclosed
Governance Achievements
- Not disclosed
Climate Goals & Targets
Long-term Goals:
- Not disclosed
Medium-term Goals:
- Not disclosed
Short-term Goals:
- Not disclosed
Environmental Challenges
- High energy usage of LLMs negatively impacting climate change.
- Inference accounts for 80-90% of machine learning workloads and demand, contributing significantly to energy consumption.
Mitigation Strategies
- Development of in-memory associative computing APU technology for flexible bit processing to reduce energy consumption in LLMs.
Supply Chain Management
Supplier Audits: Not disclosed
Responsible Procurement
- Not disclosed
Climate-Related Risks & Opportunities
Physical Risks
- Not disclosed
Transition Risks
- Not disclosed
Opportunities
- Development of energy-efficient LLMs
Reporting Standards
Frameworks Used: Null
Certifications: Null
Third-party Assurance: Not disclosed
UN Sustainable Development Goals
- Goal 7 (Affordable and Clean Energy)
- Goal 9 (Industry, Innovation, and Infrastructure)
- Goal 13 (Climate Action)
The APU technology contributes to these goals by reducing energy consumption in LLMs and promoting sustainable computing practices.
Sustainable Products & Innovation
- In-memory associative computing APU technology
Awards & Recognition
- Not disclosed