7 papers
Co-design for Trustworthy AI: An Interpretable and Explainable Tool for Type 2 Diabetes Prediction Using Genomic Polygenic Risk Scores
Ralf Beuthan, Megan Coffee, Heejin Kim +13
The polygenic risk scores (PRS) have emerged as an important methodology for quantifying genetic predisposition to complex traits and clinical disease. Significant progress has bee…
Ridgeline: A 2D Roofline Model for Distributed Systems
Fabio Checconi, Jesmin Jahan Tithi, Fabrizio Petrini
In this short paper, we introduce the Ridgeline model, an extension of the Roofline model [4] for distributed systems. The Roofline model targets shared memory systems, bounding th…
Scaling Intelligence: Designing Data Centers for Next-Gen Language Models
Jesmin Jahan Tithi, Hanjiang Wu, Avishaii Abuhatzera +1
The explosive growth of Large Language Models (LLMs), such as GPT-4 with 1.8 trillion parameters, demands a fundamental rethinking of data center architecture to ensure scalability…
ReLATE: Learning Efficient Sparse Encoding for High-Performance Tensor Decomposition
Ahmed E. Helal, Fabio Checconi, Jan Laukemann +4
Tensor decomposition (TD) is essential for analyzing high-dimensional sparse data, yet its irregular computations and memory-access patterns pose major performance challenges on mo…
Accelerating Sparse Tensor Decomposition Using Adaptive Linearized Representation
Jan Laukemann, Ahmed E. Helal, S. Isaac Geronimo Anderson +7
High-dimensional sparse data emerge in many critical application domains such as healthcare and cybersecurity. To extract meaningful insights from massive volumes of these multi-di…
PIUMA: Programmable Integrated Unified Memory Architecture
Sriram Aananthakrishnan, Shamsul Abedin, Vincent Cave +16
High performance large scale graph analytics are essential to timely analyze relationships in big data sets. Conventional processor architectures suffer from inefficient resource u…