Workload-Specific Data Movements Across AI Workloads in Multi-Chiplet AI Accelerators

By Technical Paper Link - 04 Nov, 2024 - Comments: 0

A new technical paper titled "Communication Characterization of AI Workloads for Large-scale Multi-chiplet Accelerators" was published by researchers at Universitat Politecnica de Catalunya. Abstract "Next-generation artificial intelligence (AI) workloads are posing challenges of scalability and robustness in terms of execution time due to their intrinsic evolving data-intensive characteris... » read more

Scheduling Multi-Model AI Workloads On Heterogeneous MCM Accelerators (UC Irvine)

By Technical Paper Link - 24 May, 2024 - Comments: 0

A technical paper titled “SCAR: Scheduling Multi-Model AI Workloads on Heterogeneous Multi-Chiplet Module Accelerators” was published by researchers at University of California Irvine. Abstract: "Emerging multi-model workloads with heavy models like recent large language models significantly increased the compute and memory demands on hardware. To address such increasing demands, designin... » read more

Ferroelectric Memory-Based IMC for ML Workloads

By Technical Paper Link - 21 May, 2024 - Comments: 0

A new technical paper titled "Ferroelectric capacitors and field-effect transistors as in-memory computing elements for machine learning workloads" was published by researchers at Purdue University. Abstract "This study discusses the feasibility of Ferroelectric Capacitors (FeCaps) and Ferroelectric Field-Effect Transistors (FeFETs) as In-Memory Computing (IMC) elements to accelerate mach... » read more

Chiplets For Generative AI Workloads: Challenges in both HW and SW

By Technical Paper Link - 29 Nov, 2023 - Comments: 0

A new technical paper titled "Challenges and Opportunities to Enable Large-Scale Computing via Heterogeneous Chiplets" was published by researchers at University of Pittsburgh, Lightelligence, and Meta. Abstract "Fast-evolving artificial intelligence (AI) algorithms such as large language models have been driving the ever-increasing computing demands in today's data centers. Heterogeneous c... » read more

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tag: AI workloads

Workload-Specific Data Movements Across AI Workloads in Multi-Chiplet AI Accelerators

Scheduling Multi-Model AI Workloads On Heterogeneous MCM Accelerators (UC Irvine)

Ferroelectric Memory-Based IMC for ML Workloads

Chiplets For Generative AI Workloads: Challenges in both HW and SW

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tag: AI workloads

Workload-Specific Data Movements Across AI Workloads in Multi-Chiplet AI Accelerators

Scheduling Multi-Model AI Workloads On Heterogeneous MCM Accelerators (UC Irvine)

Ferroelectric Memory-Based IMC for ML Workloads

Chiplets For Generative AI Workloads: Challenges in both HW and SW

Trending Articles

Shift Left Is The Tip Of The Iceberg

Hybrid Bonding Makes Strides Toward Manufacturability

Americas Chip Funding Energizes Industry

Advanced Packaging Driving New Collaboration Across Supply Chain

Chiplets Make Progress Using Interconnects As Glue

Knowledge Centers Entities, people and technologies explored

Related Articles

Shift Left Is The Tip Of The Iceberg

Partitioning In The Chiplet Era

3.5D: The Great Compromise

AI’s Role In Chip Design Widens, Drawing In New Startups

Key Technologies To Extend EUV To 14 Angstroms

Memory Fundamentals For Engineers

What Comes After HBM For Chiplets

Why Small Fab And Assembly Houses Are Thriving

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