arXiv subjects

Ilias Bournias

Publications and source records attributed to Ilias Bournias.

3 recordsLinked to original sources

arXiv2026

Acceleration of Data Analytics on Heterogeneous Supercloud Systems

Heterogeneous Supercloud systems are transforming data analytics by enabling scalable and efficient task distribution across diverse resources. This paper presents computational models and performance estimation techniques tailored for accelerating Dense Cholesky (CH) Decomposition and Singular Value Decomposition (SVD)-based analytics on Heterogeneous Superclouds. Our ReDSEa tool-chain automates mapping, load balancing, scheduling, parallelism, and computation overlap. Implemented on a heterogeneous system with a Huawei Kunpeng 920 ARM CPU and an Ascend 910 AI accelerator, our LLVM compiler tool-chain employs novel performance models for recursive, iterative, and blocked computations, achieving up to 17x speedup for CH and 88x for SVD over fully optimized 48-core CPU implementations.

cs.DC↗

arXiv2024

AcceLLM: Accelerating LLM Inference using Redundancy for Load Balancing and Data Locality

Large Language Model (LLM) inference on large-scale systems is expected to dominate future cloud infrastructures. Efficient LLM inference in cloud environments with numerous AI accelerators is challenging, necessitating extensive optimizations for optimal performance. Current systems batch prefill and decoding to boost throughput but encounter latency issues, while others disaggregate these phases, leading to resource underutilization. We propose AcceLLM, a novel method addressing latency and load balancing, inspired by the cache data management. It strategically utilizes redundant data to enhance inference via load balancing and optimal hardware use. Simulated evaluations on Nvidia H100 GPU and Huawei Ascend 910B2 show AcceLLM surpasses state-of-the-art systems up to 30% in latency and efficiency, handling diverse workloads effectively.

cs.DC↗

arXiv2023

ReDSEa: Automated Acceleration of Triangular Solver on Supercloud Heterogeneous Systems

When utilized effectively, Supercloud heterogeneous systems have the potential to significantly enhance performance. Our ReDSEa tool-chain automates the mapping, load balancing, scheduling, parallelism, and overlapping processes for the Triangular System Solver (TS) on a heterogeneous system consisting of a Huawei Kunpeng ARM multi-core CPU and an Ascend 910 AI HW accelerator. We propose an LLVM compiler tool-chain that a) leverages compiler analysis and b) utilizes novel performance models exploring recursive, iterative, and blocked computation models. Our tool-chain facilitates a speedup of up to 16x compared to an optimized 48-core CPU-only implementation.

cs.AR↗