TornadoVM is a programming and execution framework for offloading and running JVM applications on multi-core CPUs, GPUs, and FPGAs.
With the same code, some of your existing program code can be executed hundreds of times faster!
Juan Fumero, TornadoVM Lead Architect
Christos Kotselidis, TornadoVM Project Leader
Thanos Stratikopoulos, TornadoVM Senior Solutions Architect
Host: Erik Costlow
Production: Frank Delporte
00’36 Introduction of the guests
04’26 What is TornadoVM?
05’54 How applications can make use of the acceleration provided by TornadoVM
11’48 The difference between CPU threads and GPU instruction chain
13’42 Possible use cases for TornadoVM
15’23 Results on Apple M1
17’19 Can TornadoVM be used in cloud environments
21’18 How to use the API
24’41 Jakobs view of what would be a good match between TornadoVM and cloud usage on AWS Lambdas
AWS GPU and CPU capabilities: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/ecs-gpu.html
30’54 The complexity of GPU and FPGA programming languages and handling the differences between different architectures of GPUs, CPUs, and FPGAs
40’28 How TornadoVM could be used to heat up buildings, help to reduce the total cloud cost for companies, and run ChatGPT
43’30 Relationship between project Panama and TornadoVM
48’10 How to get started with TornadoVM
The post Foojay Podcast #17: Execute Java Code with TornadoVM on CPUs, GPUs, and FPGAs appeared first on foojay.