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Update recommendations for new release
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Harendra Kumar
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@ -1,63 +1,68 @@
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# GHC Haskell
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## Compiler Versions
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## Compiler (GHC) Versions
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GHC versions 8.0 onwards are supported by streamly per se. However, note
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that some packages we depend on (e.g. `network`) support only last three
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versions of GHC.
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For best performance use GHC 8.10 or 8.8 along with `fusion-plugin`
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(see below). Benchmarks show that GHC 8.8 has significantly better
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performance than GHC 8.6 in many cases.
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Use GHC 8.8 for best performance. Benchmarks show that GHC 8.8 has
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significantly better performance than GHC 8.6 in many cases.
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GHC versions 8.6 onwards are fully supported along with `fusion-plugin`.
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`fusion-plugin` is not supported for GHC versions below 8.6.
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GHC versions 8.0 onwards are supported without `fusion-plugin`. However, note
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that some packages we depend on (e.g. `network`) may support only last three
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major versions of GHC.
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GHC 8.2.2 may hog memory and hang when building certain applications using
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streamly (particularly the benchmark programs in the streamly package).
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Therefore, we recommend avoiding using the GHC version 8.2.x.
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## Memory requirements
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Building streamly itself may require upto 4GB memory. Depending on the
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size of the application you may require 1-16GB memory to build. For most
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applications up to 8GB of memory should be sufficient.
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To reduce the memory footprint you may want to break big modules into
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smaller ones and reduce unnecessary inlining on large functions. You can
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also use the `-Rghc-timing` GHC option to report the memory usage during
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compilation.
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See the "Build times and space considerations" section below for more
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details.
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## Compilation Options
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### Absolute Minimum
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At the very least `-O -fdicts-strict` compilation options are
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required. If these options are not used, the program may exhibit memory
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hog. For example, the following program, if compiled without an
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optimization option, is known to hog memory:
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```
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main = S.drain $ S.concatMap S.fromList $ S.repeat []
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```
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### Recommended Options
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Use the following GHC options:
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Add `fusion-plugin` to the `build-depends` section of your program in
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the cabal file and use the following GHC options:
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```
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-O2
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-fdicts-strict
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-fmax-worker-args=16
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-fspec-constr-recursive=16
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-fplugin Fusion.Plugin
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```
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Important Note: In certain cases it is possible that GHC takes too long to
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compile with `-fspec-constr-recursive=16`, if that happens please reduce the
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value or remove that option.
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Important Notes:
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1. [fusion-plugin](https://hackage.haskell.org/package/fusion-plugin) can
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improve performance significantly by better stream fusion, many
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cases. If the perform regresses due to fusion-plugin please open
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an issue. You may remove the `-fplugin` option for regular builds
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but it is recommended for deployment builds and performance
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benchmarking. Note, for GHC 8.4 or lower fusion-plugin cannot be used.
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2. In certain cases it is possible that GHC takes too long to compile
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with `-fspec-constr-recursive=16`, if that happens please reduce the
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value or remove that option.
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3. At the very least `-O -fdicts-strict` compilation options are
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absolutely required to avoid issues in some cases. For example, the
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program `main = S.drain $ S.concatMap S.fromList $ S.repeat []` may
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hog memory without these options.
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See [Explanation](#explanation) for details about these flags.
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### Using Fusion Plugin
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In many cases
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[fusion-plugin](https://hackage.haskell.org/package/fusion-plugin) can
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improve performance by better stream fusion. However, in some cases
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performance may also regress. Please note that the `fusion-plugin`
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package works only for GHC >= 8.6.
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* Add `fusion-plugin` to the `build-depends` section of your program in
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the cabal file.
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* Add the following to GHC options:
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```
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-fplugin=Fusion.Plugin
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```
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### Explanation
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* `-fdicts-strict` is needed to avoid [a GHC
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@ -103,10 +108,6 @@ Features/modules may get disabled if the kernel/OS does not support it.
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Xcode/macOS SDK installed (depends on `Cocoa` framework). However, we only
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test on latest three versions of the OS.
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## Windows
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* File system event notification module is not yet available for Windows.
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# Performance Optimizations
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A "closed loop" is any streamly code that generates a stream using
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@ -118,7 +119,7 @@ programming.
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Closed loops are generated in a modular fashion by stream generation,
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transformation and elimination combinators in streamly. Combinators
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transfer data to the next stage or combinator using data constructors.
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transfer data to the next stream pipeline stage using data constructors.
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These data constructors are eliminated by the compiler using `stream
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fusion` optimizations, generating a very efficient loop.
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