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Torsten Hoefler

4 papers hereh-index 2167 citations15 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.PF2
  • cs.AR1
  • cs.NI1
same name
  • Torsten Hoefler — 13 papers, h 8
  • Torsten Hoefler — 11 papers, h 8
  • Torsten Hoefler — 11 papers, h 9
  • Torsten Hoefler — 11 papers, h 5
  • Torsten Hoefler — 8 papers
  • Torsten Hoefler — 8 papers, h 10

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedIn-Network Collective Operations: Game Changer or Challenge for AI Workloads?

2 citations · 5 across the 4 of their papers we have counts for

collaborators

4 papers

cs.AR2026

Maia 200: A Software Defined Dataflow System for Large-scale AI Acceleration

Sherry Xu, Marco Heddes, Jackson Peng +14

We introduce Maia 200, an advanced AI accelerator delivering high performance-10 145 Tflop/s FP4 and 5072 Tflop/s FP8 within a 750W TDP and 7 TB/s HBM bandwidth. Maia exemplifies a…

cs.NI2026★ 2 cited

In-Network Collective Operations: Game Changer or Challenge for AI Workloads?

Torsten Hoefler, Mikhail Khalilov, Josiah Clark +9

This paper summarizes the opportunities of in-network collective operations (INC) for accelerated collective operations in AI workloads. We provide sufficient detail to make this i…

cs.PF2025★ 1 cited

EDAN: Towards Understanding Memory Parallelism and Latency Sensitivity in HPC

Siyuan Shen, Mikhail Khalilov, Lukas Gianinazzi +6

Resource disaggregation is a promising technique for improving the efficiency of large-scale computing systems. However, this comes at the cost of increased memory access latency d…

cs.PF2025★ 2 cited

PerfDojo: Automated ML Library Generation for Heterogeneous Architectures

Andrei Ivanov, Siyuan Shen, Gioele Gottardo +5

The increasing complexity of machine learning models and the proliferation of diverse hardware architectures (CPUs, GPUs, accelerators) make achieving optimal performance a signifi…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.