Search Results for author:
Found 8 papers, 2 papers with code
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
We introduce phi-3-mini, a 3. 8 billion parameter language model trained on 3. 3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal testing, rivals that of models such as Mixtral 8x7B and GPT-3. 5 (e. g., phi-3-mini achieves 69% on MMLU and 8. 38 on MT-bench), despite being small enough to be deployed on a phone.
Tessel: Boosting Distributed Execution of Large DNN Models via Flexible Schedule Search
This paper presents Tessel, an automated system that searches for efficient schedules for distributed DNN training and inference for diverse operator placement strategies.
Textbooks Are All You Need
Despite this small scale, phi-1 attains pass@1 accuracy 50. 6% on HumanEval and 55. 5% on MBPP.
Ranked #42 on
Code Generation
on HumanEval
TACCL: Guiding Collective Algorithm Synthesis using Communication Sketches
TACCL uses a novel communication sketch abstraction to get crucial information from the designer to significantly reduce the search space and guide the synthesizer towards better algorithms.
Scaling Distributed Training with Adaptive Summation
This paper introduces a novel method to combine gradients called Adasum (for adaptive sum) that converges faster than prior work.
EVA: An Encrypted Vector Arithmetic Language and Compiler for Efficient Homomorphic Computation
We believe that EVA would enable a wider adoption of FHE by making it easier to develop FHE applications and domain-specific FHE compilers.
Distributed Training of Embeddings using Graph Analytics
This paper presents a distributed training framework for a class of applications that use Skip-gram-like models to generate embeddings.
CHET: Compiler and Runtime for Homomorphic Evaluation of Tensor Programs
Just as the hardware ISA interface enabled hardware advances to proceed independent of software advances in the compiler and language runtimes, HISA decouples compiler optimizations and runtimes for supporting FHE applications from advancements in the underlying FHE schemes.
